Why Document Preprocessing Is the Real Engine Behind AI-Driven Advanced Manufacturing

Let’s talk about the thing that’s standing between your AI strategy and real operational transformation in advanced manufacturing: documents. Not the shiny dashboards. Not the robots on your shop floor. Not even the AI models themselves. It’s the messy, handwritten, multi-format, error-prone documents that slow everything down.

If you’re nodding your head, you’re not alone. In a recent webinar featuring Dan Matlis (President of Axendia) and Steve McCarthy (VP at Honeywell Life Sciences), the conversation zeroed in on how advanced manufacturing and AI adoption are being held back by one critical issue: the lack of intelligent document preprocessing.

So what exactly is document preprocessing, and why should you care?

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Why We’re Still Not There Yet

The life sciences industry, like many others, is facing a bimodal challenge. As Dan and Steve laid out, there’s Mode 1: the traditional problems like recalls, non-conformances, and audits. And then there’s Mode 2 (the exciting stuff): precision medicine, digital twins, bioreactors, and 3D-printed medical devices.

But the disconnect is glaring.

We’re developing revolutionary new therapies and technologies on one hand, while still relying on paper-based or PDF-based processes on the other. That’s inefficient and dangerous. As Dan said, "If you're not modernizing, you're probably out of compliance."

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The AI Bottleneck: Unstructured Data

Let’s get something straight: AI isn’t magic. It’s a system. It’s only as good as the data you feed it. And most of the data that manufacturing and quality teams deal with? It’s unstructured. Scanned PDFs. CAD files. Handwritten notes. Lab reports. Clinical trial forms. Emails. Sensor logs.

Feeding this directly into an AI model is like handing a calculus problem to someone who can’t read the numbers.

Dan put it perfectly: "You get the right answers on the wrong information."

That’s why document preprocessing is so crucial. It’s the connective tissue between your raw operational reality and your AI-driven future.

AI Can’t Help You Until Your Data Can Help It‍

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What Is Document Preprocessing?

Think of document preprocessing as your AI prep kitchen. Before you feed anything into a model, you need to:

• Clean it: Remove noise, correct skewed scans, separate overlapping text and graphics.
• Structure it: Identify tables, figures, headers, sections.
• Extract it: Pull out key fields like dates, IDs, values, measurements.
• Validate it: Apply rules, verify against expected formats or databases.
• Transform it: Normalize formats, enrich with metadata, convert to machine-readable formats.

And you need to do all of this at scale, across multiple facilities, document types, and systems.

Getting ready to lift the heavyweight of Unstructured Data: How AI helps you lift it off the ground

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Why It Matters for Advanced Manufacturing

According to Axendia’s research, implementing advanced manufacturing technologies can:

• Improve product quality (76%)
• Increase process efficiency (87%)
• Enhance regulatory compliance (60%)

But here’s the catch: These gains only happen when your data flows smoothly from one system to the next. If you’re still relying on tribal knowledge, manual validation, or "catapult"-style handoffs between departments, you’re not ready for AI. You’re not even ready for automation.

Steve called this out clearly: "A system isn’t going to fix your data problem. You’ve got to fix the data first."

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Digital Transformation Starts with Paper

This isn’t only a problem in life sciences. If your company has more than one facility, more than one legacy system, or more than one regulatory body to report to, then you’re in the same boat. You’ve got disconnected processes, siloed systems, and document chaos.

Document preprocessing isn’t about ripping everything out and starting over, but rather about bridging the old and the new. As Dan shared from his J&J days, "You don’t have to rip and replace. In today’s environment, you can add sensors, add capabilities with minimal disruption."

That’s where Adlib’s middleware architecture shines. Adlib integrates directly with your existing systems, QMS, DMS, MES, ERP, LLM, without requiring major overhauls. Adlib layers seamlessly into your tech stack, augmenting current workflows, accelerating time to insight, and dramatically improving output quality. It modernizes from within, not by dismantling, ensuring you get the benefits of automation and AI without the disruption.

And that’s the magic. You can take that lab report scanned in a rural site and turn it into AI-ready data without overhauling the whole operation.

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Avoiding the Pitfalls

Here’s what doesn’t work:

• Buying an AI platform and expecting it to clean your data for you.
• Automating a bad process and expecting good results.
• Throwing technology at the problem without redesigning the workflow.

Dan’s analogy nails it: "AI is like a hammer. You don’t go to your contractor and say build me a house with a hammer. It’s a tool, not a strategy."

Document preprocessing ensures you’re actually building a solid foundation.

The Rise of Automation-Enabled ECM: Why Static Storage Is No Longer Enough

How Adlib Turns Unstructured Data into Smart, Actionable Content

Is Your ECM Smart Enough for AI?

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Making AI More Accurate and Auditable

One of the hidden superpowers of document preprocessing? It dramatically improves the accuracy and trustworthiness of AI.

Think about:

• Prompt engineering: With clean inputs, you can write simpler, more effective prompts.
• Reduced hallucinations: Structured data keeps models grounded.
• Human-in-the-loop: Confidence thresholds allow for smart exception handling.
• Regulatory defensibility: Traceable transformations and validation logs keep auditors happy.

As Dan emphasized, "We don’t want regulators telling us how to validate AI. We need to be able to explain what we’re doing, clearly and succinctly."

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Realizing the Value

So what’s the payoff?

Steve laid it out:

• Top line: Get products to market faster.
• Bottom line: Reduce operational and compliance costs.
• Risk: Avoid recalls, improve audits, maintain brand trust.

And Dan added a fourth: resilience. The ability to pivot when the next disruption hits. Whether it’s a pandemic, a supply chain issue, or a breakthrough therapy, you want a system that can adapt.

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TL;DR: Document Preprocessing Is a Strategic Advantage

If you want:

• AI that actually works,
• Manufacturing that’s truly advanced,
• Compliance that doesn’t require fire drills,
• And a workforce that moves faster than its paper trail...

Start with document preprocessing.

It’s not sexy. But it’s essential.

AI is only as good as the documents it can read. And your future is only as scalable as the data you’re feeding it.

Let’s fix that.