How to fix the infrastructure underneath agentic document workflows
A scanned renewal form comes back with every field extracted correctly and high confidence. The one thing it misses is the “cancel” a customer handwrote across the page. In production, at scale, nobody is reading closely enough to catch it before the customer is charged.
This session explains why “mostly right” stops working at scale and lays out three practical layers to fix it. The advice is vendor-neutral, so it applies whatever tools you build with.
What you’ll learn
- Where the human safety net disappears as document volume grows
- Why field-level accuracy isn’t the same as understanding a document well enough to act on it
- Where real documents trip up large language models (LLMs): handwriting, tables, merged headers, inserted scans, and signatures
- How to decide what AI should handle automatically, what needs review, and what should stop
- How to bring reviewers into the source document with the full decision chain
Three layers for production-ready workflows
Each layer covers one part of keeping an automated document workflow reliable at scale.
Layer 1: Process documents reliably
Parse first and reason second, with structured, source-grounded output.
Layer 2: Govern automated action
Route, audit, and escalate, with the rules set before deployment.
Layer 3: Bring people in when judgment matters
Give reviewers the real document and the evidence.
Test it on your own documents
They’re the only benchmark that counts. Start a free trial(opens in a new tab).
Speaker
Greg Ives
Director of Product Marketing
Greg Ives is Director of Product Marketing at Nutrient, where he leads go-to-market strategy, product positioning, and sales enablement. With more than a decade of B2B product marketing experience, Greg has built a career on translating complex technology into clear, compelling narratives that resonate with buyers and drive revenue.