Bring Bedrock Data Automation in-house — guided by a team with 20+ years in document data extraction.

Amazon Bedrock Data Automation (BDA) turns documents, images, audio, and video into structured, usable data. But the technology is only half the project. The other half is knowing what to extract, how to validate it, and how to govern it — and that’s where two decades of extraction experience pays for itself.

We’ve watched this space evolve — we know what works

We started when extraction meant OCR — raw text off a page. Then came OCR templates, pinned to fixed layouts. Then machine learning models that could read semi-structured and unstructured documents no template could touch. Now generative AI does in seconds what used to take projects months.

We’ve worked through every one of those eras. We know which approaches hold up in production, where accuracy breaks down, and what it actually takes to get extracted data you can trust into the systems that run your business.

More than BDA blueprints

BDA blueprints are the starting point — they define what to pull from each document type. But a production extraction operation is more than blueprints:

• Custom processing pipelines — multi-stage workflows built around your document types, volumes, and downstream systems, not generic samples.
• Custom interfaces — the screens and tools your team uses to work with extracted data every day.
• Human-in-the-loop validation and oversight — confidence thresholds, review queues, and exception handling designed in from day one, because no extraction runs unattended at scale.

How we help — four ways to engage

Whether you want a second set of eyes or a team to build it with you:

1. Sharpen your current plan. Already working on a BDA project? We’ll review your blueprint architecture, pipeline design, and validation approach — and tell you what’s solid and what isn’t.
2. Create the plan together. Starting from zero? We’ll design the strategy: which document types, which blueprints, what the pipeline looks like, and how validation and governance fit.
3. Build it. We’ll implement the pipelines, integrations, and interfaces alongside your team.
4. Build your own in-house solution. Want the capability to live inside your organization? We’ll help you stand up your own BDA practice — architecture, build, and knowledge transfer so your team runs it.

AI process vs. AI governance — we know the difference

Running extraction through AI is the process. Governing it is something else entirely: who reviews low-confidence results, what gets logged, how exceptions escalate, and how you prove the data is trustworthy months later.

We build both. Every engagement includes the governance layer — human oversight, audit trails, and controls — because extraction without governance is just faster guessing.

Why MaxxLogix

• 20+ years in document data extraction — from OCR to generative AI.
• Deep working knowledge of BDA and the broader IDP market — we know the tools, the trade-offs, and what survives contact with production.
• A documents-and-data mindset: extraction is only valuable when the data lands where work gets done.

Ready to start your in-house BDA project — or fix the one you’ve started?

Contact us to talk through your documents, your goals, and the fastest path to production.

Frequently asked questions

Do we need AWS expertise in-house to start a BDA project?

No. We can lead the AWS side while your team focuses on the business requirements — or we can build your team’s capability as we go, so you own it at the end.

Can you help with a BDA project we’ve already started?

Yes. We’ll review your current blueprints, pipeline design, and validation approach, then help you close the gaps — whether that’s tuning extraction, adding human-in-the-loop review, or redesigning the pipeline.

What’s the difference between a BDA blueprint and a full extraction pipeline?

A blueprint defines what to extract from one document type. A pipeline is everything around it: ingestion, document routing across blueprints, validation and exception handling, human review, downstream integration, and governance. We build the whole thing.