Compliance doesn’t stumble over the big stuff—it gets buried in the fine print. And nowhere is that more evident than in complex COAs (certificates of analysis) packed with multi-lot data, unusual formats, and supplier-specific quirks.

These documents can arrive in every format imaginable. They might include varying lot numbers, inconsistent analyte names, different spec ranges, handwritten notes, and occasionally, entire tables of test results for multiple product lots. Managing these documents manually, or even semi-manually, has long been a tedious, error-prone process. 

Despite AI-driven automation having come a long way in the food and beverage industry, lingering skepticism still keeps many teams stuck in manual mode. In particular, a certain myth persists like a stubborn spec deviation: AI just can’t handle complex COAs, especially the multi-lot kind.

This belief has left many teams stuck with clunky, time-consuming workarounds. But here’s the truth: with today’s technology—specifically Intelligent Document Processing (IDP)—AI doesn’t just handle complex COAs. It excels at them. 

Let’s walk through where the myth came from, what’s changed, and why it’s time to rethink what’s possible in COA automation.

Complex COAs were never easy—even for machines 

When the industry first began digitizing COAs, most automation efforts relied on optical character recognition (OCR). OCR was—and still is—a foundational technology that converts scanned or PDF documents into machine-readable text. It’s a critical step in the document processing journey.

But OCR alone isn’t enough.

Where OCR helps—and where it hits a wall

OCR helps eliminate basic data entry by recognizing characters on a page. That means teams no longer have to type in every moisture value or microbial count by hand. However, OCR wasn’t built for the complexity of COAs:

• It struggles with unstructured or tabular layouts common in multi-lot documents.

• It can’t distinguish context—was “3.1” the protein value for Lot A, or Lot B?

• It can’t learn or adapt to supplier-specific nuances over time.

As a result, OCR still requires quality and compliance teams to review every document manually, validate the extracted data, and clean up errors. Even today, many companies still rely on legacy OCR tools that offer only partial relief from manual COA review.

That’s where TraceGains’ Intelligent Document Processing (IDP) rewrites the rulebook on COA processing.

How IDP handles complex COAs—including multi-lot formats

Unlike static OCR tools, IDP uses a combination of OCR plus advanced AI to go beyond simple text extraction. It doesn’t just see the words—it understands them in context. 

Here’s how IDP tackles even the most complex COAs with precision and speed: 

1. It understands structured tables and multi-lot data

COAs that report test results for multiple lots are notoriously difficult to process. But IDP can detect tabular layouts and extract each line as a unique record. Whether you receive one lot or ten in a single document, IDP maps the correct values to the right specifications—without manual intervention. 

2. It matches data intelligently to your specs

Complex COAs often use inconsistent labels or units of measure. “Protein (Dry Basis)” might be labeled differently by different suppliers, or even vary within the same vendor. IDP uses contextual pattern recognition to match data fields to your internal expectations, accounting for supplier quirks automatically. 

3. It improves with use

As we discussed in our previous blog, “AI Can’t Learn or Adapt to Supplier-Specific Variations”—yes, it absolutely can. Over time, IDP builds a more accurate picture of each supplier’s document patterns, improving precision with every COA processed. That means fewer exceptions, better compliance insight, and far less back-and-forth. 

4. It amplifies human expertise

Rather than replacing your team, IDP frees them up to focus on higher-value work. No more wasting hours copy-pasting data or second-guessing whether Lot C passed spec. With COAs automatically processed and verified, your experts can turn their attention to trend analysis, supplier collaboration, and risk mitigation—work that actually moves the needle on quality outcomes. 

Real-world impact: quality and compliance at scale

With IDP powering COA workflows, teams see real transformation: 

• Faster reviews. Multi-lot COAs that used to take hours can be verified in minutes. 

• Reduced risk. Accurate, contextual matching ensures every test result is validated against the correct specification. 

• Audit readiness. Every decision is tracked with a clear audit trail, complete with time stamps and digital traceability. 

• Proactive quality management. With more time and better data, teams can catch issues before they become problems—and build stronger supplier relationships in the process.

Let’s retire the myth: AI can handle complex COAs

We’ve moved past the days when automation meant compromise. With OCR still playing a key supporting role, IDP combines modern AI with a powerful knowledge layer to handle the kind of complexity that used to derail digital transformation. 

And yes—IDP can process complex COAs with multiple lots, varying formats, and supplier-specific inconsistencies. In fact, it’s doing it every day for teams that demand speed, precision, and scale. 

Ready to see IDP in action?

Learn how TraceGains’ Intelligent Document Processing can help your quality and compliance teams scale complex COA workflows without scaling headcount. 

And stay tuned for the final blog in our myth-busting series: “AI is a Black Box—You Can’t Trust What You See.” We’ll dig into AI transparency and show you how to validate what’s happening behind the curtain.