Node AI.06

Document AI

Invoices, forms and contracts read once, entered correctly, and checked.

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Document AI that extracts structured data from invoices, forms, contracts and PDFs into your ERP, CRM or database, with validation and human review.

The problem

Teams re-type data from invoices, purchase orders, KYC forms and contracts into business systems. It is slow, it is error-prone, and it scales only by hiring.

Template-based OCR breaks whenever a supplier changes their layout. Modern document AI reads documents the way a person does, but it still needs validation rules and a review step for the cases it is unsure about.

What we build

Extraction pipelines for invoices, receipts, purchase orders, application forms, bank statements and contracts
Validation against your master data: vendor lists, PO numbers, tax rules, totals
A review queue where staff confirm low-confidence fields instead of typing everything
Direct entry into your ERP, accounting software, CRM or database
Clause and obligation extraction from contracts, with links back to the source text

How it works

Documents arrive by email, upload or scan. A model extracts the fields, rules validate them, uncertain fields go to a reviewer, and confirmed data is posted to your system.

Step 1Sample your documentsWe collect a representative set, including the messy ones, and agree the fields that matter.
Step 2Extract and validateModels extract fields; deterministic rules check totals, formats and lookups against your master data.
Step 3Review interfaceReviewers see the document and the extracted fields side by side, with uncertain fields highlighted.
Step 4Post to systemsConfirmed records are written to your ERP or database through its API.
Step 5Measure accuracyField-level accuracy and review rates are tracked so thresholds can be tuned.

Deliverables

Extraction pipeline for the agreed document types
Validation rules and review interface
Integration with your target system
Accuracy report on a held-out sample

Typical stack

Python
LLM and agent frameworks
Google Cloud

We choose tools to fit your environment; this is where we usually start.

Ways to work with us

Build and HandoverA defined system, delivered, documented and handed to your team.Engagement Managed AI OpsOngoing monitoring, evaluation and improvement of your AI systems.Engagement Forward Deployed EngineersOur engineers inside your team until it runs in production.Engagement

Questions

Does it handle scanned and handwritten documents?

Scanned documents, yes. Handwriting depends heavily on legibility; we test on your samples and tell you what accuracy to expect before building.

What happens when it gets a field wrong?

Every field carries a confidence score. Low-confidence fields go to a reviewer, and validation rules catch inconsistencies such as totals that do not add up.

Which systems can it post to?

Anything with an API or import format: Tally, Zoho, SAP, Odoo, NetSuite, Salesforce, custom databases. We confirm during scoping.

Adjacent nodes

Part of AI & Agents.

Agentic AI systemsAgents that plan, use your tools, and wait for a yes.AI.01 APIs, integrations and workflow automationYour systems talking to each other, so people stop copying between them.PROD.03 AI-ready data foundationsClean, modelled, governed data, so AI systems give answers you can use.DATA.02

Talk to us about document AI for your business.

Send a short brief. We reply by email, usually with questions before we propose anything.