OCR inputs
Extract and validate the text, tables, and fields the workflow actually needs.
RAG · OCR · controlled action
AI agents powered by RAG and OCR.
OCR turns documents into structured inputs. RAG retrieves relevant business knowledge with source citations. AI agents use those inputs to support repeatable work under defined approval rules.
Start with OCR document processing or enterprise RAG, then add an agent only when the workflow needs to use an approved tool, route an exception, or prepare an action for human review.
OCRstructured document inputs
RAGcited business context
Humanapproval at defined points
Fullaudit trail
Design the action layer
Configure a controlled document workflow.
Choose the business role, connect only the knowledge and tools it needs, and define where human approval is required. The preview shows the workflow shape we would refine during discovery.
1 · Choose a workflow role
2 · Connect knowledge and tools
3 · Set approval rules
From answers to action
Move from grounded answers to controlled action.
A RAG assistant retrieves relevant information and cites its sources. A RAG and OCR-powered agent can use that information in a defined process without receiving unrestricted access to your systems. Retrieval quality comes first: see why legal RAG needs hybrid search.
Knowledge assistant
Workflow agent
Retrieves relevant information
Uses retrieved information in a process
Answers with citations
Routes cited output for review
Waits for a question
Responds to approved triggers
Does not change systems
Uses only approved tools
People interpret each answer
People approve at defined points
Workflow anatomy
Every document agent needs reliable inputs, grounded knowledge, and clear boundaries.
RAG knowledge
Retrieve only from approved documents and return source context with the answer.
Role and tools
Define the agent's responsibility and the limited actions it is allowed to perform.
Approvals
Require human review for sensitive, uncertain, or high-impact outputs and actions.
Evaluation
Test extraction quality, retrieval relevance, citations, exceptions, and workflow outcomes.
Iteration
Improve parsing, retrieval, instructions, and approval paths using reviewed feedback.
Where it runs
Deploy the document workflow on your terms.
Choose where documents are processed, where the retrieval index runs, and which models can access each class of data. Compare the full options on our deployment page.
Commercial model API
Fastest to launch. Uses leading hosted models, with your data boundaries, permissions, and approvals enforced around them.
Private cloud open-source
Open models in your own cloud for tighter control over data residency, customization, and long-term cost.
On-premise GPU
Runs entirely inside your network for the most sensitive workflows, full data control, and predictable cost at scale.
Controlled document automation
Add an agent where RAG and OCR need to become action.
Bring one document-heavy process. We will map the inputs, retrieval needs, tool permissions, approval path, and realistic pilot scope.