When regulations multiply faster than teams can interpret them, compliance becomes a reasoning challenge.
Across regulated industries, experts drive the process. They review new drug formulations against FDA rules, EMA standards, and country-specific requirements. They classify devices based on intended use, risk, and clinical evidence, and must comply with IVD-R. They evaluate chemicals under REACH and regional frameworks. They manage complex rules, exceptions, time limits, and national variants. And they apply their organization’s judgment: how to assess, how to interpret, and what to validate further.
The result? Experts need to deliver reasoning that’s consistent, traceable, and scalable to meet compliance obligations. Clarifeye addresses this by letting specialists build virtual teammates: AI that captures their decision-making logic and applies it on demand.
Why Complex Regulations Make the Perfect Proving Ground
Let’s talk about cosmetic regulations. They’re a great example because they capture the full complexity you see across healthcare, pharma, and medical devices: over 2,500 rules across Europe alone. Entity ambiguity where one ingredient appears under multiple names. Layered rule logic where a substance might be permitted in one form, restricted in another, and banned under specific conditions. Constant versioning with updates that change thresholds overnight.
Consider this single rule: Salicylic acid may be used up to 3% in rinse-off hair products such as shampoos, except for products intended for children under three years.
That one sentence encodes multiple dependencies: product type, concentration, age category, and exceptions. Just one of thousands. The same pattern exists in drug interaction protocols, device classification trees, and clinical trial eligibility criteria.
This is the kind of logic that needs to be structured so AI teammates can apply it the way specialists do.
The Challenge
A major consumer products company approached us: Could they build a virtual compliance teammate capable of understanding and applying European regulations at scale?
Their regulatory team was already doing excellent work. But thousands of pages of regulations, rules with nested exceptions, constant updates, and global consistency requirements demanded significant manual effort from domain specialists whose time was increasingly needed for strategic interpretation.
They needed to assess hundreds of formulations across global markets in seconds, with every decision linked to the precise rule that justified it. Assessments had to be reproducible for any historical date and seamlessly updated as regulations changed.
The question: Could AI reliably automate rule extraction, application, and updates, guided by the experts themselves?
How They Built Their Virtual Teammate: A Conversation in Plain English
The company’s regulatory specialists talked to Clara, Clarifeye’s AI guide, in plain English about how they think through compliance decisions, and that’s it.
Here’s what happened behind those conversations.
Specialists explain their logic. “When assessing a product, I first extract each ingredient, salicylic acid, for example. I check what product type it is first. I go fetch the rules associated with the ingredient and check what rules apply to its context of use. If it’s leave-on, the limit may be 0.5%. Rinse-off gets 2%, etc. But wait, is it for kids under three? Then I need to look at exceptions, warnings, etc. Everything is explained throughout the regulatory documents, which is self-explanatory, but it’s long. Rules are described precisely in certain parts, but definitions may be pages away.”
In conversations with Clara, the team simply explained how they think about rules and product assessments. Behind the scenes, Clarifeye’s structuring engine transforms these explanations into data structuration strategies, which in this specific case will end up being structured objects. Then Clara shows them a few examples and how the virtual teammate interpreted their explanation. The team tests it with real scenarios, catches edge cases, and refines through conversation. Each feedback cycle makes the virtual teammate more precise.
Clara learns the connections practitioners see instinctively. Entity resolution is the single biggest bottleneck in compliance work. Is “salicylic acid” the same as “2-hydroxybenzoic acid”? What about BHA? Practitioners navigate this instinctively. As they talked to Clara, they naturally mentioned these connections: “Oh, and the biggest problem is entity resolution. Ingredients may have different names. You should use CAS or INCI to reconcile them. For example, salicylic acid is also called 2-hydroxybenzoic acid in some databases.” The team may even point to external data or documentation to reconcile entities.
Clara captured these insights and built them into the teammate’s knowledge. When their virtual teammate makes a connection, the team validates it. “Yes, that’s right” or “Actually, you should have used this data or name instead.” Over time, feedback loops turn edge cases into reliable patterns.
The virtual teammate evolves as regulations change. As the team explained how they handle regulatory updates, Clara built this thinking into the teammate. “When a rule changes, I need to know which formulations are affected. And if someone asks about a decision from two years ago, I need to remember what the rules were then.”
Behind the scenes, Clarifeye’s versioning infrastructure tracks rule versions with timestamps. The virtual teammate can replay historical assessments and automatically detect which formulations are affected by new amendments. When regulators ask “Why did we approve this formulation in 2023?” the teammate reconstructs the exact logic with the exact rules that were in effect then.
The Results: 30 Days, 2,500 Rules, 100% Accuracy
Working with the global consumer brand, we ran a 30-day proof of concept to see how efficiently Clara could capture their logic and encode it into a real AI regulatory teammate.
Here’s what their virtual teammate could do by the end of those 30 days.
What They Built
Their virtual teammate now understands 2,500+ rules across European regulations, creating a network of 30,000+ connected regulatory concepts. When tested against their own specialist evaluations, it achieved 100% accuracy on status determinations.
Performance gains were immediate: formula assessment dropped from a few hours to tens of seconds.
When regulations updated weeks later, their virtual teammate automatically identified 85 newly prohibited substances, 68 new exemptions, and 2 UV filter updates.
Throughout the process, regulatory specialists remained at the center. They reviewed how Clara captured their rules, added interpretation notes, simulated scenarios (“What if this limit changes to 5%?”), and validated reasoning with real case data. Each conversation strengthened the teammate’s accuracy and adaptability, creating a living knowledge system that evolves with the practitioners who use it.
Why This Matters for Healthcare and Life Sciences
The regulatory complexity we’ve described isn’t unique to consumer products. Healthcare faces the same challenge at even higher stakes.
A pharmaceutical company evaluating drug-drug interactions needs to apply their specific safety thresholds, risk models, and strategic positioning. A medical device manufacturer navigating classification paths interprets “intended use” and “risk categories” through their product portfolio, clinical evidence standards, and regulatory history. A clinical operations team assessing trial eligibility applies evolving FDA guidance against institutional policies and patient safety requirements.
When a cosmetics company makes an error, they face recalls and fines. When a pharmaceutical or medical device company makes an error, patient safety is at risk. This is why Clarifeye is built for ultraspecialization, auditability, and traceability. The platform provides consistent infrastructure: the data model, graph structure, reasoning framework, and versioning system. But each company builds virtual teammates that reflect their interpretation of regulations, their risk appetite, their strategic decisions.
Drug safety officers build virtual teammates that evaluate compound interactions against global regulatory databases, but the teammate learns their company’s specific safety thresholds. When regulatory agencies ask “How did you assess this interaction in 2023?” the virtual teammate reconstructs the exact logic with the guidelines that were current then and the internal standards their team was applying.
Regulatory specialists at medical device companies build virtual teammates that navigate classification trees, but the teammate learns from every edge case their team validates. Ambiguous classification decisions that used to require senior review become reliable patterns the teammate can apply consistently across the organization.
Protocol designers build virtual teammates that assess eligibility criteria. When FDA guidance changes, the virtual teammate automatically flags which active trials are affected. It applies the same judgment their team would use to determine which protocols need immediate review versus routine updates.
The infrastructure is the same across companies. Each virtual teammate encodes the decision-making logic of the specialists who built it, and operates on that company’s data only.
The Bottom Line
Your specialists build virtual teammates that understand how your company thinks. Clarifeye provides the infrastructure: a system where rules are structured, logic is auditable, and institutional knowledge is encoded.
From cosmetics to pharma, medical devices to clinical operations, regulatory teams scale their professional judgment without losing the nuance, critical thinking, and traceability that compliance demands.
Interested in seeing how this applies to your regulatory domain? Book a demo to explore what ultraspecialized AI could look like for your organization.
Clarifeye is an AI reasoning platform that helps domain specialists build production-ready virtual teammates. We specialize in regulated industries where precision, traceability, and professional oversight are non-negotiable.