Your document types
Assess layouts, languages, image quality, tables, and handwritten content against a representative sample.
Turn complex documents into organized, usable information. Extract what matters, check it against your rules, and give your team a clearer path to review.
Extract information. Check the details. Surface the exceptions.Example: a new request reaches a custom agent, which connects company knowledge and prepares a task for human review.
“I’d like to check my claim status.”
“Let’s find the right next step.”
Move beyond copying information from one screen to another. We build document workflows that combine extraction, validation, and human review around the documents you actually receive.
Capabilities shaped by your use case,
with the controls your business needs.
Assess layouts, languages, image quality, tables, and handwritten content against a representative sample.
Extract the fields and relationships your workflow needs, with references back to source content.
Check outputs against defined rules, flag missing or inconsistent data, and route exceptions to reviewers.
Deliver reviewed information in the formats your downstream systems need, with a traceable processing history.
Receive documents through approved channels.
Identify relevant fields and their source context.
Apply checks and surface inconsistencies.
Confirm exceptions and send structured output.
Illustrative architecture. The final workflow is designed around your requirements.
Potential applications, not completed
client projects or guaranteed outcomes.
Organize invoices, forms, and supporting documents into a structured review pack, with missing information highlighted.
Extract relevant information from financial statements and application documents to support an analyst’s review.
Capture invoice fields, check them against business rules, and send exceptions to the appropriate reviewer.
We agree on success criteria before development, test against representative examples, and make limitations visible. Useful evidence beats impressive claims.
Our approach to building AIField-level extraction quality
Performance across document types and layouts
Exception detection and reviewer workload
Traceability to original document content
A little clarity goes a long way.
We start with your actual sample documents. PDFs, scans, images, tables, and mixed layouts may need different techniques. Scope and acceptance criteria are agreed after reviewing representative examples.
Not without evidence from your documents and task definition. We agree on field-level metrics, test against a held-out sample, and document limitations before making rollout decisions.
Not automatically. The workflow should distinguish routine cases from exceptions, with appropriate review for uncertain information and decisions that require human judgment.
Tell us what’s slowing your team down.
Let’s explore what a better way could look like.