The day you put your own logo on an acquired product, you become legally responsible for packaging you have almost certainly never seen the paperwork for. This does not come up in the deal room. It comes up in week three, when someone asks where the technical file for a particular carton is and the answer turns out to be a converter whose contract ended at close.

The most common packaging challenges in mergers and acquisitions are inherited compliance liability, approved artwork held by third parties, duplicate pack specifications, harmonizing regulatory copy across two portfolios, transferring extended producer responsibility registrations, and consolidating print suppliers. The unfortunate part is, almost all of them surface after close, when the integration clock is already running – but the good news is, there are ways to get ahead.

Who is Responsible For Packaging Compliance After an Acquisition?

Under the PPWR, the practical test for who counts as the manufacturer is whose brand appears on the packaging. If it is yours, the obligation to sign the Declaration of Conformity and hold the supporting technical documentation is yours, and you are the party auditable by market authorities. That responsibility stays with you even where a supplier or converter carried out the conformity assessment and prepared the file.

This matters at the exact moment an acquisition becomes visible on shelf. The day you rebrand an acquired product, you become the manufacturer of its packaging for PPWR purposes and inherit the evidence burden for it – every substance test result, recycled content claim, and material breakdown behind the declaration.

Most packaging diligence checklists were written before August 2026 and ask about volumes, formats, and supplier contracts. Very few ask to see the technical documentation. If it does not exist, or exists only in fragments across the seller's supply chain, you find out after you own it.

Where is Approved Packaging Artwork Actually Stored?

In most regulated manufacturers, print-ready artwork sits with design agencies, repro houses, and printers, and the acquired business holds reference PDFs rather than editable source files.

The contracts holding those relationships together frequently terminate at close. So the practical position on day one is that you own a SKU list, a set of flat PDFs, and no working files – while the people who can produce a corrected pack are no longer engaged. Establishing where every approved asset physically lives, and who has the right to release it, is worth doing during diligence rather than during your first regulatory change.

What Happens to Duplicate SKUs and Pack Specifications?

Portfolio rationalization gets treated as a commercial decision, but it is a data problem first. After close you hold two pack format libraries, two sets of dielines, two substrate specification systems, and two symbol libraries – and the two sides describe the same physical pack in incompatible terms.

You cannot rationalize what you cannot compare. Before anyone can decide which of two near-identical cartons survives, someone has to establish that they are near-identical, which means normalizing two specification vocabularies into one. That work is unglamorous, sits on the critical path for every synergy target attached to packaging, and is almost never scoped.

How Do You Harmonize Regulatory Copy Across Two Portfolios?

Harmonization is usually framed as process and culture alignment. In packaging it is narrower and considerably more expensive: two companies phrase the same warning differently, hold different translation sets, use different symbol conventions, and make subtly different claims about equivalent products.

Someone has to decide which version wins, per phrase, per market. That is a regulatory decision, repeated at scale, and it needs regulatory affairs sign-off rather than design sign-off. Teams that treat it as a branding exercise discover the difference at the first audit.

Do EPR Registrations Transfer When a Brand Changes Hands?

Extended producer responsibility registrations are held by a registered producer entity in each member state, not by the brand. A change of ownership generally requires action in every market where the packaging is placed, rather than transferring automatically with the asset.

The gap between close and completed re-registration is the exposure. Product continues moving; the obligation to report and pay against it has to sit with somebody, and transition service agreements do not always say clearly which somebody.

What Changes in a Divestiture or Carve-Out?

Everything above, run in reverse and under a harder deadline. You are stripping your identity off packs you no longer own while assembling artwork packages for a buyer, against a transition services clock set during negotiation rather than by anyone who has done a packaging migration.

Divestitures also expose asset custody faster than acquisitions do. You cannot hand over what you cannot locate, and the discovery that a printer holds your only editable file for a divested brand tends to arrive late.

Where the Obligations Sit

Getting ahead of it

The pattern across all six is the same: packaging obligations are attached to data that no one has consolidated, and the deal timetable assumes that consolidation is quick. It is quick only where a single source of truth already exists.

Kallik's Veraciti™ platform is built for exactly this position – bringing artwork, specifications, and regulatory content into one governed system so that a change of ownership becomes a data operation rather than a rebuild. If you are heading into a transaction and want to talk through what integration would actually involve, get in touch.
 

If the FDA published the fragrance allergen rule tomorrow morning, how long would it take you to update every affected label? Not to work out which ones are affected. To actually change them, route them for approval, and get them to print.

Most people we put that question to can't answer it, because the question has simply never needed answering before, because regulators used to arrive with a date attached, and a date lets you build a plan around it.

Right now though? There's no date and there's barely an agency to ask either, so you’d be forgiven for feeling a little stressed and uncertain if you work in the cosmetics space right now.

What FDA Leadership Changes Mean for Cosmetics Brands

We speak to regulatory and packaging teams across the sector regularly, and the tone has shifted noticeably this year. People aren't confused about what's coming – they've read the same information as everyone else. Instead, they’re stuck waiting to see when that set of obligations will land eventually, on a schedule set by an agency in the middle of its own upheaval, hitting product ranges that in some cases run to thousands of SKUs.

We’ve heard it described as packing for a trip without knowing the destination or the departure date. You know you'll need to move fast, but you just can't do anything with that knowledge yet.

Why Delayed Regulations Increase Labeling Workload and Risk

Delay often feels like relief, like the pressure is off and you can take a step back. In actual fact, it’s the complete opposite.

Every month a rule sits unpublished, the eventual compliance window doesn't get longer. It gets denser. The work doesn't evaporate during the wait. Instead it accumulates, then arrives in a single lump, competing with the launches, seasonal packs, and market variants already sitting in your queue.

So the thing worth focusing on isn't the date. It's the lag: the number of days between a rule landing and your last affected label being approved and out the door.

That number belongs entirely to you. It's determined by how your labeling operation is built, and unlike the FDA's timetable, you could change it – and it’s probably quicker and easier than you think!

What Slows Down Cosmetics Label and Artwork Updates

The thing slowing down cosmetic label and artwork updates is rarely the change itself, but rather finding the change and making it accurately. When label content lives inside artwork files, every ingredient statement is a separate object. Update one allergen declaration across 800 SKUs and you're opening 800 files. Answering "which of our products contain this?" becomes a manual audit rather than a search.

Then there's sign-off. Approval routed through email and shared drives is slow at normal volumes and falls over at high ones. Version control gets fuzzy, people chase, and eventually someone approves the wrong proof. Structured artwork approval fixes this by making the route itself the record, so the audit trail builds as people work rather than being reconstructed from inboxes six months later.

Cloud-based label and artwork systems matter more here than they might sound like they should. Regulatory work is distributed now. A supplier in one country, a reviewer in another, a print partner somewhere else again. Everyone needs the current version, not a current version.

Put those pieces together and the shape of the problem changes. Label content becomes reusable components rather than text welded into a file. One approved change flows through to every product that uses it. Where-used search returns the affected list in seconds instead of weeks. A regulatory update stops being an event and becomes a task.

Is Labeling Software Worth the Investment?

We get it, managing emails and spreadsheets is practically free, whereas investing in software can be costly. It’s true, enterprise labeling software is a real investment and the payback doesn’t happen immediately.

But look at what the alternative really costs. We’re talking about the hours spent hunting SKUs, the rework when an outdated ingredient list reaches print, and the launches held up because artwork is stuck behind a compliance scramble. Nevermind the reputational, monetary and even life-threatening consequences of a recall! Reality is, those costs are being paid by your business right now, just spread thinly enough that nobody puts them on a line item. And the volume of regulatory change heading toward this sector isn't going to make them smaller.

Moving Legacy Labels Into a New System Without the Pain

If cost isn’t your objection to making the move, we can almost bet the migration process is what’s holding you back. Nobody wants to hand over a decade of legacy artwork and hope it comes out the other side intact.

If that's the thing holding you back, it's worth knowing our platform uses a migration tool called AToM to handle exactly this. It reads your existing labels and artwork and converts them into structured, reusable content, which turns onboarding from a multi-year manual slog into something considerably shorter and a great deal less painful.

Preparing for FDA Changes Without a Deadline

Here's the short version of all this. The uncertainty is real, and it isn't going away soon. But the reality is, setting the regulation date was never the part you controlled. What you control is what happens the day after it's announced. Whether that day means a room full of people opening artwork files one at a time, or a where-used search, one approved change, and a normal week.

That difference isn't down to how well your team knows the regulations. It's down to whether your label content is structured, your approvals are traceable, and your system is accessible to everyone who needs it. Get those three things right and regulatory change stops being an emergency.

The teams that will handle the next FDA announcement calmly are already making that change now, while there's no deadline forcing them to. That's the advantage of the current lull. You can't control when the FDA moves, but you can control whether that day is a scramble or just a Tuesday.

If you’re ready to make the move and transform your label and artwork management for the better, speak to one of our experts. Call us on +44 (0) 1827 318100, email enquiries@kallik.com, or fill in a form here.

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Packaging artwork failures cost regulated manufacturers far more than reprinting labels. A single labeling error in pharma, medical devices, or chemicals can trigger recalls, regulatory fines, and serious patient safety risks. According to a 2026 Fonteum analysis of FDA enforcement data, labeling and packaging issues are among the top reasons for device recalls. Kallik helps regulated manufacturers prevent these failures through packaging artwork management built for compliance-first workflows.

Why Packaging Artwork Failures Happen in Regulated Industries

Most artwork failures trace back to fragmented processes, not careless people. When teams rely on email threads, spreadsheets, and disconnected tools to manage label content, version confusion becomes inevitable. A regulatory affairs team might approve one version of a label text while the design team works from an outdated file.

Cross-functional complexity makes things worse. Artwork approvals in regulated manufacturing typically involve regulatory affairs, quality assurance, marketing, legal, and packaging engineering. Each stakeholder reviews different elements, and without a single source of truth, conflicting edits and missed updates slip through.

Translation and localization add another layer of exposure. A product sold across 30 markets needs 30 language-specific label variants, each with region-specific regulatory content. One missed dosage unit change or an incorrect hazard symbol can result in non-compliance across an entire product line.
 

The Real Cost of Getting Artwork Wrong

The consequences of artwork failures extend well beyond the cost of reprinting. In the FDA's enforcement database, labeling and packaging errors rank as a leading reason for device recalls. For drug products, recall-related disruptions can reduce after-tax profits significantly when products ship late.

Regulatory penalties add up quickly. Non-compliance with standards like EU CLP or FDA 21 CFR Part 211 can result in fines, warning letters, and market withdrawal. Then there are the indirect costs: lost retailer contracts, supply chain disruptions, and the slow erosion of brand trust that follows a public recall.

Where Artwork Workflows Break Down

Three breakdown points appear repeatedly in regulated artwork workflows. First, content sourcing errors occur when approved regulatory text is not properly linked to the artwork file. Designers may pull from an outdated source document, introducing discrepancies that reviewers miss because they are checking layout, not content accuracy.

Second, approval bottlenecks form when review cycles run in sequence rather than in parallel. In some organizations, a single label change can take weeks to move through five or six approval stages. This delays product launches and increases the pressure to cut corners late in the process.

Third, version control gaps create the conditions for the most dangerous errors. Without governed artwork management, teams may accidentally release a pre-approval version to print. In regulated industries, that kind of failure can trigger a Class I recall.
 

How to Prevent Artwork Failures Before They Start

Prevention starts with centralizing your artwork and label content in a single governed platform. When all regulated text, symbols, translations, and design files live in one controlled environment, you eliminate the version confusion that causes most errors. Kallik's Veraciti platform gives you this kind of centralized control, connecting label content directly to artwork workflows so that every change is traceable.

Structured approval workflows are equally important. Configurable, role-based review paths ensure the right people review the right elements at the right stage. Parallel review capabilities reduce cycle times without sacrificing rigor. And built-in audit trails capture every action, so you can demonstrate compliance during inspections without scrambling for documentation.

Automated change propagation closes the remaining gap. When a regulatory update affects a specific phrase or symbol, an integrated platform can identify every label and artwork file that uses that content and flag them for review. This kind of impact analysis is what separates reactive error correction from proactive failure prevention.

Building a Failure-Proof Artwork Operation

Technology alone does not solve the problem, unfortunately. You also will need clear process governance. Define ownership for each stage of the artwork lifecycle: who initiates a change request, who reviews regulatory content, who gives final quality approval, and who authorizes print release.

Integrate your labeling platform with upstream systems like ERP, PLM, and regulatory information management tools. When product data flows automatically into your labeling system, you remove the copy-paste operations that introduce human error at scale.

Finally, treat your artwork operation as a strategic function, not an administrative task. The organizations that invest in structured, governed artwork workflows are the ones that bring compliant products to market faster, avoid costly recalls, and maintain the regulatory confidence their customers and patients depend on.

How to Protect Your Artwork Process from Failure

Packaging artwork failures in regulated manufacturing are preventable. They start with fragmented processes and disconnected tools, and they end with recalls, fines, and lost time. By centralizing content, structuring approvals, and automating change propagation, you can build an artwork operation that delivers compliant labeling every time.

Ready to change your label and artwork management process for the better and prevent failures for good? Speak to one of our experts by emailing enquiries@kallik.com, calling +44 (0) 1827 318100 or filling in a form.
 

There's a lot of noise right now about what AI can do for labelling and artwork management. Less is being said about what it can't do: turn messy, fragmented data into something trustworthy.

That's the warning Kallik is putting out to regulated industries this month. As the global leader in enterprise labelling and artwork management software, working with brands including Kenvue, Cardinal Health and Procter & Gamble, we're seeing a pattern that worries us: companies under pressure are adopting AI tools before they've sorted out the "operational basics." And in pharma, med device, and other highly regulated sectors, that gamble carries real consequences.

The squeeze that's driving the rush

It's not hard to see why teams are reaching for AI. Regulatory overhauls across the US and Europe are approaching fast, skills shortages are leaving already-stretched teams struggling to manage increasingly complex product lifecycles, and there's constant pressure to protect margins while getting products to market quickly.

Faced with all that, automation looks like the obvious answer. AI tools promise to handle intricate labelling updates, multi-language translations and shifting regulations at a pace manual, under-resourced teams simply can't match. The problem isn't the ambition. It's what happens when that ambition meets poor foundations.
 

Panic buying meets fragmented data

We're calling it panic buying for a reason: businesses are deploying AI checking mechanisms on top of siloed, inconsistent data, and that combination opens the door to serious compliance errors.

Gurdip Singh, CEO of Kallik, puts it bluntly: "There's a massive amount of noise in the market right now about what AI can do, but trying to run autonomous agents over poor legacy data is creating a compliance timebomb. One that pharma and med device manufacturers will absolutely want to avoid."

It's not an isolated concern either. A recent NVIDIA enterprise study found that 48 percent of leaders rank data-related issues as their single greatest challenge to successful AI implementation. As Gurdip puts it: "You can't build a skyscraper on quicksand."

What actually goes wrong

When an AI tool queries unchecked, fragmented data, it starts connecting the wrong dots. That might mean silently dropping a European date format into a US template, or subtly altering a mandatory font.

In a low-stakes environment, that's an annoyance. In pharma or med device labelling, it's a different story entirely. A tiny hallucination like that can break the entire chain, triggering compliance failures, reputational damage and multi-million-pound product recalls, each one putting patients at risk.

This isn't a fringe issue, either. A global Gartner study found that fewer than 28 percent of AI initiatives meet ROI expectations, largely because of poor data quality. Most either fail outright or get quietly abandoned within 12 months.

Fixing the foundation first

This is why Kallik built its approach around data before automation, not the other way round. Our innovative migration tool, AToM (Assisted Tool of Migration), is a pure AI-driven engine that intelligently reads and extracts data from legacy formats at the onboarding stage, eliminating the manual input errors and duplicates that feed AI hallucinations in the first place.

That clean, accurate data then feeds directly into Veraciti™, our cloud-native single source of truth. Veraciti™ atomises content into pre-approved, version-controlled building blocks within a central asset and phrase manager. Because the data layer is fully structured, Veraciti™ stays entirely vendor-agnostic, so enterprises can securely plug and play any corporate LLM or external AI tool into a validated environment via secure APIs.

"We still continue to see businesses storing their data in spreadsheets or on old, outdated software, either updated by several different people across various departments, or by no one at all," Gurdip says. "So if you don't know what 'language' your data speaks, or whether it's the very latest version of information, your AI certainly won't."
 

The stress test regulated industries can't afford to fail

Gurdip concludes: "This new wave of AI adoption in the industry feels like a new kind of stress test. Advanced automation can easily handle massive data migrations and instant multi-language updates at lightning speed, but it requires an absolute single source of truth to pull from. Without that ironclad data, you are effectively letting an autonomous system fly blind into a regulatory storm."

For regulated industries, the message isn't "don't adopt AI." It's "don't adopt it on top of a mess." Get the data foundation right, and automation becomes a genuine advantage rather than a hidden liability.

We've spent years inside exactly this problem with global, regulated manufacturers. If your team has ever quietly wondered whether "organized" and "audit-ready" are actually the same thing, this is worth twenty minutes of your time before you commit to an AI roadmap, not after. 

Find Out If You're Actually AI-Ready →

Most labeling operations aren't disorganized. They're organized at the edges and improvised in the middle. And that gap is exactly what's standing between them and genuine AI readiness.

Why the middle stays messy even in mature teams

This isn't a failure of effort. It's a structural side effect of how labeling operations grow. A company starts with one product line and one market, and a shared drive is genuinely fine. Then it's ten markets, then fifty, then a few thousand SKUs, each with its own regulatory quirks, language requirements, and approval chain. Nobody sits down one day and designs for that scale. It arrives gradually, and the tools that worked at the start get patched, not replaced.

The result is a labeling operation that's a patchwork of genuinely good systems stitched together with manual work. A proper label management platform for the master content. A separate tool for artwork. Email for approvals that don't fit either. A spreadsheet somewhere that's become load-bearing, even though nobody would admit it in a steering committee.

Regulators have seen the consequences of this for years. Mislabeling and packaging errors are a routine, repeatable cause of product recalls, not a rare edge case, and the pattern behind them is almost always the same: disconnected data, a manual handoff that should have been automatic, unclear ownership at the point of change, or a version that slipped through because nobody could see it had already been superseded. None of that shows up on an org chart. It shows up in the middle.

Why AI makes this worse before it makes it better

Here's the part that catches most teams off guard. Artificial intelligence and automation don't fix a messy middle – they amplify it.

Think of it like handing a very fast, very literal assistant the keys to your current process. If your approved content, your translations, and your regulatory rules already live in one governed place, that assistant becomes genuinely useful: it can flag the label variant affected by a rule change, draft the update, and route it to the right reviewer, all before a human would have finished searching for the source file. If your approved content is scattered across drives, inboxes, and someone's "final_v3_ACTUAL" folder, that same assistant will happily automate the confusion. It will move faster, with more confidence, in exactly the wrong direction.

This is the uncomfortable truth behind most AI readiness conversations. The question was never "do we have access to AI tools." Most companies do, or will within a year. The real question is whether the foundation underneath them, the data, the ownership, the audit trail, can support automation without quietly multiplying the risk. Gartner's recent research into enterprise disruptors points at exactly this shift: domain-specific AI models and digital trust platforms are moving up the priority list, precisely because generic automation on top of ungoverned data creates more exposure, not less.

A useful way to picture it: a tidy desk doesn't tell you anything about the drawer underneath it. Plenty of labeling operations have a tidy desk – dashboards, KPIs, a clean-looking process map for the auditors. The drawer is where the real work happens, and it's rarely as tidy as the desk suggests.

What "AI-ready" actually looks like in a labeling operation

Genuine AI readiness in this world isn't about which tool you've licensed. It's about whether four things are true at the same time:

One source of approved content

Not "the system we mostly use." One place where the current, approved version of every piece of content lives, with everything else pointing back to it.

Traceable ownership at every handoff

When content moves from drafting to regulatory review to market approval, it should be obvious who owns the next decision, without a Slack message asking "does anyone know where this is at."

A complete, inspection-ready audit trail

Not reconstructed after the fact from email search. Available, by default, showing what changed, who approved it, and which markets and products it touched.

Rules that apply themselves

When a regulation changes for one market, the system should be able to show exactly which labels are affected, rather than relying on someone remembering to check.

Companies that get this right see the difference in very concrete terms. Diversey, for example, needed to control thousands of multilingual labels across more than fifty countries without adding another layer of manual oversight.

By bringing content, approvals, and artwork workflows into one governed system, the business now manages around 13,000 European artworks in a single place and has doubled artwork capacity across Eastern Europe without adding headcount. That's not a story about buying an AI tool, but rather a story about fixing the middle first, so that automation had something solid to build on.
 

The honest self-check most teams haven't done

Here's the thing about the messy middle: it's genuinely hard to see from inside your own organization. You know your systems. You know the workarounds so well they stopped feeling like workarounds years ago. The gap between "we feel organized" and "we could survive an audit, a recall, or an AI rollout without finding a nasty surprise in the middle" isn't something a dashboard shows you.

That's the exact gap we built our AI Readiness Guide to close. It's a practical way to see where your labeling operation genuinely stands: what's solid, what's improvised, and what would break first if you tried to automate on top of it today. There's a short self-assessment too, so instead of guessing, you get a straight answer about where the real risk sits.

We've spent years inside exactly this problem with regulated manufacturers, which is honestly the only reason we could build something this specific. If your team has ever quietly wondered whether "organized" and "audit-ready" are actually the same thing, this is worth twenty minutes of your time before you commit to an AI roadmap, not after.

Find Out If You're Actually AI-Ready →

Ask ten people in a boardroom what "AI" means and you'll get ten different answers. Most of them will be confident. Most of them will also be wrong, or at least incomplete. And in an industry where a mislabeled product can mean a recall, a regulatory breach, or worse, "close enough" isn't a great place to be operating from.

Here's the thing nobody wants to say out loud: a huge amount of what gets marketed as "AI" right now is nothing of the sort. It's automation with better branding. Sometimes it's machine learning dressed up to sound more impressive than it is. And sometimes it's genuinely nothing at all beyond a logo on a slide deck and a line in a sales pitch. That's not a dig at the technology. It's a dig at how it's being sold.

The name-drop problem

Walk the exhibition floor at any regulatory or compliance conference and count how many times you hear "AI-powered" in the space of an hour. Now ask how many of those companies can tell you, in plain terms, what their AI actually does, why it's AI rather than something simpler, and what changes for the customer as a result. The silence is telling.

This matters because somewhere above most of the people reading this article, a board has decided AI is strategic. Which means somewhere below them, someone has been told to "go and use AI," and now has to work out what that actually means in practice.

JT, who's well versed in the nuances of legal, compliance, and regulatory affairs teams from his client engagement work here at Kallik, has a line about this that's stuck with us: "It's like being told to go and buy six cars. Okay, which ones? For what? A fleet of vans is not the same as six sports cars, but from the outside, 'buy six cars' sounds like one simple instruction. AI is the same. It's not one thing. It's a category, not a decision." 

So the board says "AI." Does that mean they've got a defined use case, solving a real problem for real customers? Or have they seen a competitor's PR machine in action and started worrying their own USP is looking thin? Often nobody's stopped to ask. And vendors who lean into that vagueness rather than resolving it aren't doing anyone any favours. They're helping a nervous procurement team tick a box marked "innovative" for the next board update, quietly hoping nobody asks what's underneath it.

So what's actually the difference?

Let's clear this up properly, because it's genuinely not complicated once someone explains it without an agenda.

Automation is rules doing what rules are told to do. If X happens, do Y. No learning, no judgment, no adaptation, just consistent, reliable execution of a process a human has already defined. Automation is often the least glamorous of the three and also, for a lot of regulated businesses, the one that delivers the fastest and most measurable return. Think: a label change automatically triggering the right approval route in every market it touches, without someone manually checking a spreadsheet to work out who needs to sign off in Brazil versus Germany.

Machine learning is where things start learning from data rather than following fixed rules. It spots patterns across large volumes of information and gets better, or at least different, as it sees more of it. This is powerful for things like flagging anomalies in artwork data or predicting where a compliance bottleneck is likely to occur based on historical patterns. It's not thinking, but rather pattern recognition at a scale humans can't match by hand.

Artificial intelligence is the broader, more ambitious category: systems designed to perform tasks that would typically require human judgment. This is where things like content generation, contextual decision support, and adaptive recommendations live. It's also the term that gets stretched the thinnest, because "AI" sounds better in a pitch deck than "if-then logic," even when if-then logic is what's actually running under the hood.

None of these is inherently better than the others. That's the part that gets lost. The right answer depends entirely on the problem you're trying to solve, and that's exactly where most conversations about "getting AI" go wrong before they've even started.

"People don't know the difference, and they don't know what they need"

This is the sentence JT comes back to more than any other when he talks about the conversations he has day to day: "Most people who come to us have already been told to 'do something with AI' before anyone's worked out what problem they're solving. They don't know the difference between AI, ML, and automation, and that's fine, that's not their job to know. But it means the first conversation we have usually isn't about technology at all. It's about working backwards from what's actually slowing them down."

That backwards approach matters more than it sounds. Because the honest answer to "what AI should we buy?" is very often: none of it, yet. What you need first is clarity on the problem. Then the right technology, whichever category it falls into, becomes obvious.

Choosing the tool for the job, not the job for the tool

This is where the industry-wide temptation to lead with AI becomes a genuine risk rather than just an irritating buzzword habit.

If a business rushes to implement an AI solution before understanding whether the underlying problem is actually a data quality issue, a process bottleneck, or a plain lack of automation, it ends up with an expensive, complicated answer to a question nobody asked properly.

The better sequence looks like this:

1. Define the actual bottleneck. Not "we need AI," but "approvals for market-specific artwork take three weeks longer than they should, and nobody can see why."
2. Work out what's causing it. Manual, repetitive steps that don't need human judgment? That's automation territory. Patterns across huge volumes of data that no person could reasonably track? That's machine learning. Genuine, complex decision support that needs contextual reasoning? Now you're talking AI.
3. Match the technology to the problem, not the other way round.
   It's a less exciting process than announcing an AI initiative to the board. It's also the one that actually delivers something.

The part that doesn't get said enough

None of this is a case against AI. Used well, in the right place, for the right reason, it's genuinely transformative, particularly for regulated industries drowning in complexity across multiple markets, products, and approval chains. Automation and machine learning have quietly been doing serious heavy lifting in artwork and label management for years, long before "AI" became the word everyone reached for.

The problem has never been the technology. It's the habit of treating it as a single, interchangeable thing you can buy off a shelf to satisfy a board slide, rather than a set of very different tools, each suited to a very different job. Get that distinction right first, and the rest of the conversation gets a lot easier.

Where to go from here

Any AI is only as good as the data behind it. That's why Kallik's approach starts with the problem, not the tech: what's the scale of the issue, is your data sitting in silos that need connecting, and only then, is AI, ML, or automation actually the right answer? Layering AI over a spreadsheet or bolting it onto your PLM or ERP as a plug-in isn't a strategy, it's a hope. Our engineering team has spent years building AI, machine learning, and automation into our end-to-end, cloud-based software, Veraciti™, on foundations that are properly cemented first, and with compliance and data accuracy never an afterthought.

If you're trying to work out which of the three you actually need, that's a conversation worth having before you buy anything. Why not speak to JT yourself to understand where your business can improve its label and artwork management process with the right tools. Call +44 (0) 1827 318100, email enquiries@kallik.com or fill in a form here.

FAQs: Artificial Intelligence, Machine Learning, and Automation 

Most label and artwork errors are blamed on people. Someone used the wrong file, a reviewer missed a comment, or a regulatory change failed to reach every affected market.

Look a little closer, however, and there is usually a manual handoff behind the mistake. An artwork was downloaded from one system and uploaded into another, feedback moved into an email chain, or a new version was created without everyone knowing it existed. As a result, each handoff creates a small gap in control – which across a global enterprise that manages thousands of labels, can quickly lead to a serious compliance risk. 

We recently asked Veraciti™ experts Ed Briggs and Tear Hambrey about the labeling and artwork challenges they see most often. Their answers highlighted an issue that deserves more attention: many enterprises have digitized individual tasks without connecting the full process. Watch the full conversation below.

The handoff is where control starts to disappear

Tear identified manual processes, limited collaboration, and manual handoffs as some of the biggest challenges enterprises face when managing labels and artwork. That does not necessarily mean these companies lack technology. In many cases, they have several systems supporting different stages of the process.

Product information may sit in one platform, while artwork is created in another. Reviews happen through email or a separate proofing tool, approved files are stored elsewhere, and local teams maintain their own spreadsheets or folders.

Each tool might perform its individual job perfectly well, bringing a false sense of security, when reality is that the problem begins when files, information, and decisions move between them.mWhich version was transferred? Were all the comments included? Who approved the final change? Does the asset stored in one platform match the artwork being reviewed elsewhere?

A process can appear highly digital while still relying on people to maintain the links between disconnected systems. When those links are informal, traceability becomes patchy and errors become much harder to prevent.

Where should enterprises start?

Tear’s advice is to look at the entire process rather than focusing only on the final artwork. Follow one artwork from the initial brief and design stage through review, approval, release, and future updates. Pay particular attention to each point where a file, decision, or piece of data moves between people or systems.

Ask:

• Where are files downloaded, re-uploaded, or sent by email?
• How do reviewers know they are working from the latest version?
• Where are comments and approval decisions recorded?
• Can the business see who changed what and when?
• How would teams find every label affected by a regulatory update?

These questions reveal whether the process is genuinely controlled or simply held together by experienced people who know how to navigate it. That distinction becomes particularly important when label volumes increase, regulations change at scale, teams restructure, or a key employee leaves.

How Veraciti™ closes the gaps

Veraciti™ brings artwork design, content, assets, collaboration, approvals, and traceability into one cloud-based label and artwork management platform. Its value is not simply that it digitizes existing tasks. By connecting each stage, Veraciti™ helps teams retain the context, evidence, and control that can otherwise disappear during manual handoffs.

• Approval Workflow allows reviews to follow a defined, role-based process, with comments, annotations, decisions, and actions captured in a complete audit trail.
• Cloud Designer brings template-based artwork creation into the same controlled environment, helping teams connect design more closely with collaboration and governance.
• Where Used allows users to identify every artwork containing a particular phrase, symbol, image, or managed asset. When a regulatory change arrives, teams can understand its impact without searching through thousands of files manually.

Together, these capabilities help create a connected process in which teams can see how an artwork was created, reviewed, approved, and changed.

Stop digitizing tasks in isolation

Adding another tool to one stage of the process may solve an immediate problem, but it can also introduce another handoff.

Enterprises need to look beyond individual features and consider how artwork, approved content, decisions, and evidence move through the complete labeling lifecycle. If that movement cannot be followed clearly, the process is not as controlled as it might appear.

This is where Veraciti™ stands apart. Its capabilities operate as connected parts of one governed process, helping enterprises reduce manual intervention, strengthen traceability, and manage global labeling change with greater confidence.

This is the first article in our series with Ed and Tear. In the coming weeks, we will look more closely at AToM, Approval Workflow, Cloud Designer, Where Used, and the other Veraciti™ capabilities helping enterprises solve specific labeling and artwork challenges.

Watch the full conversation with Ed and Tear, or request a Veraciti™ demo to see the platform in action. If you're thinking about how to build that foundation in your labeling and artwork operations, Kallik’s label and artwork platform is designed to do exactly that. Get in touch to find out more by calling +44 (0) 1827 318100, emailing enquiries@kallik.com or filling in a form here.

Cooper is an 18-month-old chihuahua from Tamworth who recently ate a hosta – a common, easy-to-grow garden plant sold in garden centres and high street shops across the UK. Within hours, he was seriously ill.

His owner, Caitlin Roberts, immediately took him to the vet, who struggled to figure out what was causing the illness. It wasn't until an X-ray revealed a blockage that the cause became clear: toxins from the plant had built up in his system. As a result, Cooper needed emergency surgery which has left him requiring specially adapted food for the rest of his life.

The cost of a missing warning

Caitlin's vet bill came to £9,000. However, had she not acted fast, this could’ve cost Cooper’s life. As she told BBC News, the hardest part wasn't the cost – it was not knowing. "They're not just dogs, are they? They're like your babies," she said.

That’s the reality when it comes to failing to properly label hazardous products, it can cost a lot more than just money, reputation and trust, but lives.

Why this happened

Hostas are widely sold as one of the best foliage plants for UK gardens due to being easy to grow and low maintenance. Vet Gabriel Wax, who treated Cooper, pointed out that hostas are far from the only risk: lilies, daffodils, and tulips can all be dangerous too. The real problem though, is that none of these plants are required to say that they’re dangerous.

There's currently no legal requirement in the UK for plant retailers to label toxicity to pets at the point of sale. A shopper can walk out of a garden centre with a plant that could seriously harm their dog or cat, with nothing on the label to tell them.

A simple fix, already underway

Caitlin has launched a Change.org petition, now signed by more than 500 people, calling for two things: a clear toxicity warning on plant labels, and the Animal PoisonLine number printed alongside it. 

Our CEO, Gurdip Singh, spoke to the BBC about why this kind of change is realistic, not aspirational: "A lot of people probably don't realise the label is what really keeps you safe. It tells you how to use a product, what it should be used for, and the health hazards around it as well."

He drew a direct comparison to how far human allergen labelling has come in recent years, giving shoppers clearer, more actionable safety information at the point of purchase: "Companies around the world work to strict regulations and have systems in place. This is just about putting further information onto the label to enable the consumer to be better informed."

Why this matters to us

We work with some of the world's biggest brands across pharma, life sciences, cosmetics, and chemicals, helping them manage exactly this kind of information: accurate, compliant, up-to-date labelling at scale. It's easy for labelling to look like paperwork from the outside, but stories like Cooper's are a reminder that it's rarely just paperwork. For someone standing in a garden centre with no other way of knowing what's safe, the label is the warning – or the gap where one should be.

Caitlin's petition is still open for signatures. If you think plant labels should carry pet safety warnings too, you can find it linked in the full BBC News story.

If you work in medical device labeling, you already know that 2026 has brought significant regulatory changes. Between the FDA's Quality Management System Regulation (QMSR) and mandatory EUDAMED modules in the EU, the rules around labeling have shifted dramatically. Cloud labeling software helps you navigate these requirements by centralizing your assets, automating approvals, and maintaining the audit trails that regulators expect. Kallik Veraciti gives medical device manufacturers a single platform to manage labels and artwork across global markets.

This blog walks you through everything you need to know about enterprise labeling and artwork management software for medical devices. You'll learn what cloud labeling software does, how to evaluate your options, and how to implement workflows that keep you compliant while accelerating your time to market.

 

Key Takeaways: Cloud Labeling Software for Medical Devices in 2026
 

• Cloud labeling software centralizes your medical device labeling assets, giving you a single source of truth across all markets and products.
• 21 CFR Part 11 and EU Annex 11 compliance requires audit trails, electronic signatures, and validated systems that cloud platforms can deliver.
• Automated approval workflows reduce label cycle times by eliminating email chains and enabling role-based reviews with full traceability.
• Kallik’s software helps medical device manufacturers reduce label change cycles by up to 70% while ensuring EU MDR and FDA compliance.
• Choosing the right cloud labeling software requires evaluating integration capabilities, validation support, and regulatory feature sets carefully.
   

What is Cloud Labeling Software for Medical Devices

Cloud labeling software is a platform that lets you create, manage, approve, and distribute medical device labels through a web-based system. Rather than storing files on local servers or sharing artwork through email, you access everything through a secure online environment. This approach centralizes all your labeling assets, from symbols and regulated phrases, to translations and artwork files – all in one location. Your team members access the same current versions regardless of their physical location. Changes propagate instantly across your entire product portfolio.

How Cloud Labeling Differs from On-Premise Solutions

Traditional on-premise labeling systems require you to install software on your own servers. You manage the hardware, handle security updates, and coordinate access for remote team members.

Cloud platforms eliminate that infrastructure burden. Your vendor hosts the system, manages security, and handles uptime. You log in through a browser and get to work. For medical device companies with facilities across multiple continents, this means your team in Asia can approve the same label that your regulatory specialist in Europe just updated and without VPN complications or server synchronization delays.

Core Capabilities of Cloud Labeling Platforms

Modern cloud labeling software typically includes several key functions. Asset management lets you store and organize all your labeling components. Workflow automation routes labels through predefined approval paths. Version control tracks every change with timestamps and user attribution.

Integration capabilities connect your labeling platform to other enterprise systems like PLM, ERP, and QMS. Reporting tools let you pull audit data quickly when regulators come calling. These features combine to create an end-to-end system that handles your entire label lifecycle.

Why Medical Device Manufacturers Need Cloud Labeling Software in 2026

The regulatory environment for medical device labeling has grown more demanding over the past several years. Cloud labeling software addresses these challenges directly by building compliance features into your daily workflows.

FDA QMSR and 21 CFR Part 11 Requirements

The FDA's transition to the Quality Management System Regulation (QMSR) aligns 21 CFR Part 820 with ISO 13485:2016. For your labeling operations, this means tighter requirements around documentation, traceability, and validated processes.

21 CFR Part 11 specifically governs electronic records and electronic signatures. Your cloud labeling system must capture who made each change, when they made it, and why.

Electronic signatures require two distinct identification components, typically a user ID and password. The system must link signatures to specific records and maintain complete audit trails that regulators can review.

EU MDR and IVDR Labeling Obligations

The EU Medical Device Regulation (MDR) and In Vitro Diagnostic Regulation (IVDR) have introduced extensive new labeling requirements. Your labels must now include specific symbols from EN ISO 15223-1:2021, Unique Device Identifiers (UDI), and detailed manufacturer information.

MDR Annex I Chapter III Section 23.2 lists every element that must appear on your device labels. Cloud labeling software helps you manage this complexity by storing approved phrases, symbols, and translations centrally. When regulations change, you can update affected content once and push changes across all relevant labels.

Managing Global Labeling Complexity

Medical device companies selling internationally face labeling requirements that vary by market. Language translations, country-specific symbols, and regional regulatory statements all need tracking and management.

A cloud platform gives you visibility across your entire portfolio. You can quickly identify which labels need updates when a regulation changes or when you enter a new market. This centralized approach prevents the inconsistencies that lead to compliance gaps and potential recalls.

Essential Features to Look for in Cloud Labeling Software

When evaluating cloud labeling software for your medical device organization, certain features distinguish platforms built for regulated industries from generic design tools.

Audit Trails and Electronic Records Management

Your system must generate computer-generated, time-stamped audit trails for every action that creates, modifies, or deletes a record. These trails should capture the user who performed the action, exactly what changed, and the reason for the change.

The audit trail must be protected from alteration or deletion. During regulatory inspections, you'll need to export this data in human-readable formats quickly. Look for systems that let you filter audit data by date range, user, asset, or batch number.

Electronic Signature Capabilities

21 CFR Part 11 requires that electronic signatures include two distinct identification components. The signature must display the signer's printed name, the date and time, and the meaning of the signature (such as "reviewed," "approved," or "author").

Authority checks should verify that users have permission to perform the specific step they're signing for. The system should detect and flag any unauthorized changes after signing. These controls ensure that your electronic approvals carry the same legal weight as handwritten signatures.

Role-Based Access Controls

Not everyone on your team needs the same access to your labeling system. Role-based access control lets you assign permissions based on job responsibilities. A designer might be able to create and edit artwork, while a regulatory specialist can only approve or reject.

This segregation of duties prevents conflicts of interest and ensures that critical actions require appropriate authorization. Session timeouts and automatic account lockouts add additional security layers. Regular access reviews help you identify and remove excessive privileges before they become compliance issues.

Workflow Automation and Approval Routing

Automated workflows route labels through predefined approval sequences without manual coordination. When a designer finishes a label, the system automatically notifies the next reviewer. Deadlines and reminders keep projects moving forward.

Parallel reviews let multiple stakeholders review simultaneously rather than waiting in sequence. This capability can significantly reduce your label cycle times. Kallik's medical device labeling software includes configurable workflows that adapt to your organization's specific approval requirements.

Integration with Enterprise Systems

Your labeling platform should connect with other business systems where product data lives. API availability lets you pull device attributes from your PLM or ERP automatically, eliminating double-entry and reducing transcription errors.

Integration with quality management systems ensures that CAPA activities and label changes stay synchronized. Legacy system compatibility matters if you're migrating from an existing platform. Evaluate how easily you can import your current label library and historical data.

Understanding Medical Device Labeling Compliance Requirements

Compliance requirements for medical device labeling span multiple regulatory frameworks. Understanding these requirements helps you configure your cloud labeling system appropriately.

FDA UDI System Requirements

The FDA's Unique Device Identification system requires that every medical device distributed in the United States carry a UDI. This identifier has two parts: the Device Identifier (DI), which identifies the specific version or model, and the Production Identifier (PI), which includes lot number, serial number, expiration date, and manufacturing date.

Your labels must include machine-readable formats like barcodes – either GS1 or HIBC standards depending on your chosen issuing agency. The UDI must also appear in human-readable plain text. Class III devices and implants have the most stringent requirements, while Class I devices have more limited obligations.

EU UDI Requirements Under MDR and IVDR

The European Union has implemented its own UDI requirements under MDR Article 27. Devices must carry UDI carriers on labels, and manufacturers must submit UDI data to the EUDAMED database as applicable modules become operational.

IVDR introduces similar requirements for in vitro diagnostic devices. The phased implementation timeline means different device classes face different compliance deadlines. Your labeling system needs to track these requirements and alert you when deadlines approach.

ALCOA+ Principles for Data Integrity

Regulators expect your electronic records to meet ALCOA+ standards. Data must be Attributable (traceable to a specific user), Legible (readable and accessible), Contemporaneous (recorded at the time of the activity), Original (preserved as originally captured), and Accurate (complete and error-free).

The "plus" adds Complete, Consistent, Enduring, and Available. Your cloud labeling system should enforce these principles automatically through its design. Audit trails address attribution, version control maintains originals, and backup systems ensure enduring availability.

Step-by-Step Guide to Implementing Cloud Labeling Software

Moving to a cloud labeling platform requires careful planning. This step-by-step approach helps you manage the transition while maintaining compliance throughout.

Step 1: Assess Your Current Labeling Process

Start by documenting how your labeling process works today. Map out every step from initial design request through final production approval. Identify who touches each label, where bottlenecks occur, and how long each stage typically takes.

Catalog your existing labeling asset (symbols, phrases, templates, and artwork files). Note where these assets currently live and how different team members access them. This inventory becomes your migration checklist later.

Step 2: Define Your Requirements and Evaluation Criteria

Based on your current state assessment, define what your new system must accomplish. Distinguish between must-have features and nice-to-have capabilities. Consider your regulatory requirements, team size, number of products, and geographic distribution.

Create a vendor evaluation checklist that covers compliance features, integration capabilities, validation support, and user experience. Include questions about the vendor's experience with medical device customers and their regulatory expertise.

Step 3: Evaluate Vendors and Select Your Platform

Request demonstrations from vendors on your shortlist. Watch for how their systems handle specific scenarios you face – mass label changes, multi-language management, or complex approval routing.

Ask about validation documentation. Vendors serving regulated industries should offer accelerator packages including user requirements specifications, functional requirements specifications, and installation qualification scripts. These documents speed your validation but don't replace your responsibility to validate the system in your intended use.

Step 4: Plan Your Implementation Phases

Break your implementation into manageable phases. Many organizations start with a pilot involving a limited product line or geographic region. This approach lets you work out issues before full rollout.

Define clear success criteria for each phase. Establish who owns the project, what resources they need, and how you'll handle issues that arise. Build in time for training and documentation at each stage.

Step 5: Migrate Your Existing Label Library

Migrating your existing labels and assets takes careful attention. Verify that every symbol, phrase, and artwork file transfers correctly. Check that version histories and approval records remain intact.

Some platforms offer AI-driven digitization that can accelerate this process. These tools read existing labels and extract components into structured, searchable formats. The investment pays off through faster updates and better reuse of approved content.

Step 6: Configure Workflows and User Permissions

Set up your approval workflows to match your organization's needs. Define roles and assign appropriate permissions. Configure notification rules so team members know when actions require their attention.

Test your workflows thoroughly before going live. Create test labels and route them through your full approval process. Verify that audit trails capture everything correctly and that signatures appear where required.

Step 7: Train Your Team and Document Procedures

Effective training covers both system operation and regulatory requirements. Users need to understand why certain controls exist, not just how to click through them. Role-specific training ensures that designers, reviewers, and administrators each know their responsibilities.

Document your standard operating procedures for the new system. Include step-by-step instructions for common tasks and guidance for handling exceptions. Keep this documentation accessible and update it when processes change.

Step 8: Validate Your System

System validation demonstrates that your software operates as intended and meets regulatory requirements. Following vendor documentation helps but doesn't eliminate your validation obligations. You must validate the system in your specific intended use.

A risk-based approach focuses validation effort where it matters most—systems that impact product quality and patient safety. Document your validation activities thoroughly. Maintain evidence that tests passed and that any deviations were addressed appropriately.

Step 9: Go Live and Monitor Performance

Plan your cutover carefully. Some organizations run parallel processes temporarily, using both old and new systems until confidence builds. Others switch completely at a defined date.

Monitor key metrics after going live. Track label cycle times, error rates, and user adoption. Address issues quickly and adjust workflows based on real-world experience. Schedule regular reviews to identify improvement opportunities.

Best Practices for Medical Device Labeling Workflow Automation

Automating your labeling workflows delivers the biggest benefits when you design them thoughtfully. These practices help you maximize efficiency while maintaining compliance.

Design Workflows Around Your Actual Process

Map your approval workflows to how decisions actually happen in your organization. Forcing an artificial sequence creates frustration and workarounds. If your regulatory and quality reviewers typically work in parallel, configure parallel review steps.

Build in escalation paths for when someone is unavailable. Define backup approvers and timeout rules that prevent single individuals from becoming bottlenecks. Test these edge cases before they happen in production.

Use Templates and Component Libraries

Templates and reusable components dramatically accelerate label creation. Build approved symbol libraries, standard phrase collections, and pre-validated layout templates. When designers start from approved building blocks, they spend less time on repetitive work and make fewer errors.

Kallik Veraciti manages regulated content including text, symbols, translations, and claims centrally. This ensures consistency across your product portfolio and simplifies updates when regulations change.

Implement Automated Quality Checks

Configure your system to check for common issues automatically. Barcode validation ensures scannability before labels reach production. Spelling and grammar checks catch typos. Symbol placement rules verify that required elements appear where regulations specify.

These automated checks complement human review rather than replacing it. They catch obvious problems early so reviewers can focus on substantive evaluation rather than proofreading.

Track Metrics and Continuously Improve

Measure what matters: average cycle time, number of revision rounds, on-time completion rates, and error detection at each stage. These metrics reveal where your process works well and where improvements would have the most impact.

Schedule periodic process reviews with your labeling team. Ask what's working, what's frustrating, and what they wish the system could do. Small adjustments based on real user feedback add up to significant improvements over time.

How Kallik Veraciti Supports Medical Device Labeling Compliance

Kallik has spent over 20 years helping medical device manufacturers manage labeling and artwork processes. The Veraciti platform addresses the specific challenges that regulated industries face.

Single Source of Truth for All Labeling Assets

Veraciti centralizes your symbols, phrases, translations, and artwork in one cloud-based repository. Every team member works from the same current versions. When you update a symbol, that change flows through to every label using it.

The platform's "where used" functionality lets you quickly identify every label affected by a change. This visibility is critical when regulations change or safety information requires updates across your portfolio.

Automated Artwork Generation and Mass Change Management

Kallik's automated artwork generation tools create compliant labels from your approved content and templates. When you need to make changes across hundreds or thousands of labels, mass change capabilities let you apply updates uniformly rather than editing each file individually.

Medical device companies report reducing label change cycles by up to 70% after implementing Veraciti. This acceleration comes from eliminating the manual coordination that slows traditional processes.

Built-In Compliance for EU MDR, FDA, and Global Regulations

Veraciti includes features specifically designed for regulatory compliance. Full audit trails track every action. Role-based approval flows ensure proper authorization. Electronic signatures meet 21 CFR Part 11 requirements.

The platform supports EU MDR, IVDR, FDA UDI, FDA 21 CFR 820, 21 CFR Part 11, and EU GMP Annex 11 compliance. This regulatory coverage helps you manage requirements across multiple markets from a single system.

Cloud-Native Architecture on AWS

Veraciti runs entirely on Amazon Web Services with extensive security and compliance certifications. Cloud-native design means you get 24/7 availability, automatic backups, and access from anywhere your team works.

This infrastructure eliminates the IT burden of managing servers and security updates internally. Your team focuses on labeling work rather than system administration.

Common Challenges in Medical Device Labeling and How to Overcome Them

Even with strong systems, medical device labeling presents ongoing challenges. Understanding common issues helps you address them proactively.

Managing Multi-Language Labels

Products sold in multiple countries require translated labels. Managing dozens of language versions creates version control complexity and increases the risk that translations fall out of sync with source content.

Cloud labeling platforms address this by linking translated content to source phrases. When you update the source, the system flags all translations for review. Centralized translation management ensures consistency and simplifies the coordination with translation vendors.

Handling Regulatory Changes Across Multiple Markets

Regulations evolve constantly. New symbol requirements, updated safety statements, or changed UDI obligations can affect large portions of your label portfolio.

Effective platforms give you tools to assess regulatory impact quickly. You can identify affected labels, plan your update sequence, and track progress toward compliance deadlines. Automated alerts notify you when regulatory changes require attention.

Coordinating Approvals Across Teams and Time Zones

Global organizations often have approvers in different locations. Time zone differences can add days to approval cycles if you're waiting for sequential reviews.

Configure your workflows to enable parallel reviews where possible. Set clear expectations for review turnaround times. Use automated reminders to keep projects moving. These practices minimize delays without compromising review quality.

Integrating Acquisitions and New Product Lines

Medical device companies frequently grow through acquisitions. Each acquired company brings its own labeling systems, processes, and asset libraries. Integrating these into a unified platform takes planning and execution.

Cloud platforms simplify this integration because they don't require local infrastructure at each facility. You can onboard new sites quickly and migrate their assets into your centralized system. Standardized processes then ensure consistency across your expanded organization.

Future Trends in Medical Device Labeling Technology

Labeling technology continues to evolve. Understanding emerging trends helps you make decisions that position your organization well for the future.

AI and Machine Learning in Label Management

Artificial intelligence is beginning to change how organizations manage labels. AI-driven digitization can read existing labels and extract content into structured formats, accelerating migration from paper or file-based systems.

Machine learning algorithms can detect anomalies in label content, identify potential compliance issues, and suggest improvements based on patterns in your data. These capabilities augment human reviewers rather than replacing their judgment.

Electronic Instructions for Use (eIFU)

EU Implementing Regulation 2025/1234 expanded the scope of devices eligible for electronic Instructions for Use. For many professional-use devices, you can now deliver IFU content electronically rather than printing paper inserts.

This shift offers environmental benefits and cost savings while improving information currency. Your labeling system should support eIFU workflows including QR code generation, website hosting, and paper fallback procedures for devices that still require physical IFUs.

Enhanced Supply Chain Integration

Greater integration between labeling systems and supply chain partners continues to develop. Contract manufacturers, packaging suppliers, and logistics providers increasingly expect digital connections that eliminate manual handoffs.

API-based integrations let you share approved label files and production data securely with partners. This connectivity reduces lead times and ensures that your supply chain prints labels from controlled, current specifications.

In Conclusion: Choosing the Right Cloud Labeling Software for Your Medical Device Organization

The right cloud labeling software becomes a strategic asset for your medical device organization. It accelerates your time to market, reduces compliance risk, and gives your team tools that make their work easier rather than harder.

Focus your evaluation on the features that matter for regulated industries: audit trails, electronic signatures, role-based access, and validated workflows. Look for vendors with genuine experience in medical device labeling – the regulatory nuances matter.

Consider how the platform will grow with you. Your product portfolio will change, regulations will evolve, and your organization will expand into new markets. Choose a partner committed to adapting their platform alongside these changes.

Cloud labeling software represents an investment in operational excellence. When you centralize your labeling assets, automate your workflows, and build compliance into your daily processes, you create a foundation that supports your business objectives while protecting patient safety.
 

Frequently Asked Questions About Cloud Labeling Software for Medical Devices in 2026

The label on your product tells an important story that greatly influences buying decisions. However, it's rarely the whole story.

Behind every finished product is a chain of decisions, materials, suppliers, and processes that most companies struggle to see clearly themselves – let alone communicate to customers, regulators, or the next link in the supply chain. Therefore, digital product passports haven’t created a new problem, but they have highlighted one that's always existed. This is where the opportunity comes in.

What a digital product passport actually does

Let’s start with the basics: what is a digital product passport (DPP)? A digital product passport (DPP) is a structured digital record that travels with a product throughout its lifecycle, right from beginning to end. Accessed via a QR code, NFC tag, or similar data carrier, it stores verified information on where materials came from, how the product was made, its carbon footprint, how it can be repaired, and how it should be recycled.

Introduced under the EU's Ecodesign for Sustainable Products Regulation (ESPR), DPPs will become mandatory for certain product categories from 2027, starting with batteries, with phased expansion across electronics, textiles, construction materials, and more through to 2030. But the regulatory timeline is almost beside the point.

The real question DPPs are asking

Across regulated industries such as pharma, chemicals, consumer goods, and medical devices, product data is often fragmented across systems, held in spreadsheets, duplicated across markets, and manually managed at scale. The result is poor traceability, slow updates, and a constant risk of errors reaching the market.

Digital product passports ask companies to do something straightforward but demanding: know your product, end to end, and be able to prove it. That's a question that compliance teams, labeling managers, and supply chain leaders have been grappling with long before Brussels mandated an answer. DPPs now give that question a formal structure.

For businesses that have already invested in centralizing and controlling their product data, the DPP is validation. For those still managing product information in silos, it's the forcing function they probably needed.

Why DPPs are good for regulated industries

There's a tendency to view any new regulation as an additional cost layer. But DPPs are unusual in that the structured, accurate, centrally managed product data they require, is the same infrastructure that improves operations regardless of compliance obligations.

When a company can accurately track exactly which materials went into which products, across which markets, updated in real time, they're not just DPP-ready. They're better positioned to manage recalls, respond to supplier changes, support sustainability reporting, and handle the kind of rapid regulatory updates that have become a fact of life in global markets.

The circular economy goals embedded in ESPR reflect where consumer expectations, investor scrutiny, and procurement criteria are already heading. DPPs give businesses a credible, verifiable way to demonstrate that their products are what they say they are. That's not a compliance cost, but rather a market advantage.

The labeling connection most companies miss

There's one aspect of DPP readiness that often catches businesses off guard: the relationship between digital product data and physical labels. Regulatory markings, safety information, and required product details still need to appear on-pack. What a DPP does is create a parallel digital layer of product information, accessible via a data carrier that has to appear on the physical label itself.

That makes DPP compliance a major labeling challenge. QR codes and NFC tags need to be integrated into label design and print workflows. Product data needs to be accurate, current, and consistent between what's on the label and what's in the digital record. Any reformulation, supplier change, or market-specific regulatory requirement that requires information to be updated, now has to flow correctly through both.

For organizations managing hundreds or thousands of product labels across global markets, that coordination demands a structured, scalable approach to labeling and product data management from the outset.

Getting ahead of the curve

Businesses selling into the EU have a window right now to build DPP readiness properly The companies that do this well will have cleaner data, faster update cycles, and stronger traceability across their supply chains.

Ultimately, digital product passports ask a simple question: can you stand behind every claim your product makes? If you’re unsure where to start, Kallik can help. Speak to one of our labeling and artwork experts today by visiting the How Kallik Works page, getting in touch with our team at enquiries@kallik.com, or filling in a form here.

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