AI & Automation
AI Document Processing
Turn invoices, forms, contracts and PDFs into structured data — extracted, classified, validated and posted into your systems — so your team stops typing what a machine can read.
AI Document Processing: the overview
Every business handles a flood of documents — supplier invoices, order forms, receipts, applications, contracts — and most still process them by hand: someone reads each one and types it into a system. That’s slow and error-prone. AI document processing reads those documents and turns them into clean, structured data.
We build the pipeline around your document types and your systems: capture (email, upload, scan), extraction and classification with AI, validation against your rules, and posting into your ERP, accounting or operations system. Where a document is unclear or fails a check, it is routed to a person, so uncertain data is reviewed before it reaches your systems.
The result is less manual data entry, faster turnaround for routine documents, and fewer keying errors reaching your systems. Because it is built around your documents, rules and systems, it can be tuned as new layouts and suppliers appear, with accuracy re-measured on your test set after each change.
What AI Document Processing includes
Capture & Intake
Ingest documents from email, upload, scanners or your systems.
Extraction & Classification
AI reads and classifies documents and extracts the fields you need.
Validation & Rules
Extracted data checked against your business rules and records, with confidence scoring.
Human-in-the-Loop
Low-confidence or exception documents routed to a person for review.
System Posting
Validated data posted into your ERP, accounting or operations system; see ERP integration.
Audit & Storage
Original documents stored and linked, with a full processing audit trail.
Who AI Document Processing is built for
Finance & AP teams
Automate supplier invoice and receipt processing into accounting.
Operations & logistics
Turn order forms, delivery notes and paperwork into structured data.
High-volume document handlers
Applications, claims and forms read and validated automatically, with exceptions sent to staff.
Anyone re-keying documents
Replace manual data entry with validated extraction and human review of exceptions.
Is AI document processing the right choice?
A good fit when
- You process a steady volume of similar documents (invoices, delivery notes, forms) and someone re-keys them.
- The fields you need are consistent, even if layouts vary by supplier or sender.
- Extracted data must be checked against your rules or records, such as purchase orders or customer accounts, before posting.
- You can provide a sample of real documents, including the difficult ones.
Consider another option when
- Your ERP or accounting system already offers invoice capture that handles your suppliers; try it first.
- Volumes are low; manual entry may cost less than building and running a pipeline.
- Documents already arrive as structured data (EDI or e-invoices); direct system integration is more reliable than reading PDFs.
Usually in a first release
- Two or three document types from your highest-volume source
- Capture from one channel, such as a shared inbox, upload or scanner folder
- Extraction, validation rules and confidence scoring for the agreed fields
- A review screen for exceptions and low-confidence documents
- Posting into one system, such as your ERP or accounting package, with an audit trail
Outside the first release unless agreed
- Handwriting, additional languages or document types not in the agreed sample
- Posting into additional systems beyond those agreed
- Changes to retention or archiving in your document management system
- Tuning for production volumes before the pilot is approved
Anything outside the approved scope is reviewed and agreed before work begins. See how we work.
Data, controls, responsibilities and ownership
Data migration and integrations
- We document which data goes to which model provider for each workflow, and keep personal or sensitive fields out of prompts where the task does not need them.
- Commercial model APIs offer business terms and data-retention settings that vary by provider and account type. We configure the settings you choose and record them; see security and data protection.
- Where your policy requires it, open-weight models hosted in your own cloud account or on your own servers are an option. They usually mean more hosting effort and can be less accurate on hard cases, so we compare them on your test set before you decide.
- Posting depends on your ERP or accounting system’s API or import format, and an integration user your team controls.
- Original documents are stored in storage you own, linked to the record they created, for the retention period you set.
Roles, approvals and audit
- Review thresholds
- Each field has a confidence threshold; anything below it, or any document that fails a rule, goes to a reviewer before posting.
- Validation before posting
- Totals, tax, supplier, purchase order and duplicate checks run against your records before anything is written.
- Evaluation before go-live
- Field-level accuracy is measured on a labelled test set of your own documents and re-measured after any change to prompts, models or rules.
- Audit trail
- Each document’s extraction, edits, reviewer and posting result is logged and linked to the original file.
What we need from your team
- A sample of real documents, including difficult ones, with the correct values for the agreed fields so they can be labelled.
- The validation rules your team applies today, including the exceptions.
- API or import access to the system documents are posted into.
- Reviewers who handle exceptions during the pilot and rollout.
- Model provider and storage accounts in your organization’s name.
Ownership, support and running costs
- Project code, prompts, configuration and evaluation sets transfer to you on full payment, and your data and documents are yours throughout. Third-party foundation models remain the provider’s and are used under the provider’s terms; see our IP and ownership policy.
- Model provider, hosting and storage accounts are set up in your organization’s name where possible, so usage, retention settings and terms sit between you and the provider.
- Running costs by category: model or API usage (grows with volume and input length), vector index and storage, application hosting, evaluation upkeep when your content or the model changes, and monitoring. Amounts depend on volume, model choice and hosting.
- Providers update and retire models. A maintenance and support agreement covers re-running your evaluation set and adjusting prompts when that happens.
Related reading for this decision
- AI agent development
When extraction is one step in a longer workflow with lookups, decisions and approvals.
- ERP integration services
How extracted data is posted into an ERP safely, with validation and error handling.
- Workflow automation
For the approval and routing steps around document handling.
- Security and data protection
How documents and extracted data are stored, accessed and retained.
How we deliver AI Document Processing
Custom software built around the way your business works. Five steps, with a free pilot of 2 to 3 key modules before the full build.
Step 1: Understand
We learn how your business works.
Your requirements, workflow, challenges and goals, understood before anything is recommended.
Step 2: Plan
We design the right solution around your workflow.
Modules, workflows, roles, approvals, reports and integrations, agreed before development.
Step 3: Select Technology
Choose the right technical foundation.
Technology options matched to your users, security, budget and growth, not one fixed stack.
- Free pilot
Step 4: Pilot
Test our work before full project development.
Free. You choose 2 to 3 key modules and we build them first, so you can judge our work.
The full project starts only after you approve the pilot.
- Full project
Step 5: Build & Scale
From approved pilot to complete digital system.
Full development, testing, deployment, training and support, built to grow with you.
Guides for this decision
In-depth, practical reading for teams planning this kind of project.
- Guide · 11 min readIntelligent Document Processing for Invoices, Forms and Contracts: How It WorksIntelligent document processing reads invoices, forms and contracts, extracts the fields you need, checks them against rules and your own records, and sends doubtful cases to a person. This guide explains each stage, where it fails and how to measure it on your own documents.Read the guide
- Guide · 9 min readHow to Evaluate an AI Pilot Before Rollout: Test Sets, Metrics and a Go/No-Go ScorecardAn AI pilot is ready for rollout when it meets acceptance criteria you set in advance, on a test set built from your own data, including the hard cases. This guide covers metrics by task type, human review thresholds, failure-mode testing and a go/no-go scorecard.Read the guide
AI Document Processing FAQ
Invoices, receipts, purchase and order forms, delivery notes, contracts, applications and general PDFs and scans — structured and semi-structured documents where consistent data needs to be extracted.
It depends on your documents: layout variety, scan quality, handwriting and language all affect it. We measure field-level accuracy on a labelled test set of your own documents before go-live, set confidence thresholds below which a person reviews the document, and re-measure after changes. We do not quote an accuracy figure before seeing your documents.
Yes, where the system offers an API or import format. Validated data is posted through it, and documents that fail validation or fall below the confidence threshold wait for a reviewer instead of being posted.
They are routed to a person for review (human-in-the-loop). The system handles routine documents and involves staff for the exceptions, and reviewer corrections are logged so recurring problems can be fixed.
The pilot measures extraction accuracy on a sample of your own documents and shows the review and posting flow working with your system. It does not prove accuracy on document types or suppliers missing from the sample, behaviour at full production volume, or running cost at scale. Those are checked in a controlled rollout after you approve the full build, with accuracy re-measured on live documents.
Often, yes. Options include OCR and extraction models hosted in your own cloud account or on your own servers, or a commercial provider whose business terms and retention settings meet your policy. Self-hosted options usually mean more hosting effort and can be less accurate on difficult documents, so we compare them on your test set before you decide.
Project code, prompts, configuration, validation rules and the evaluation set transfer to you on full payment, and your documents and data are yours throughout, with no per-document fees from us. Third-party foundation models remain the provider’s and are used under the provider’s terms, and open-source components stay under their own licences, as our IP and ownership policy sets out.
See working software before you commit
Before you commit to the full project, we build 2 to 3 of your key modules as working software, free of charge. Your team tests the pilot, and the full build starts only after you approve it.
See how the free pilot worksUnderstand
We learn your requirements and how your organisation works today.
Select pilot modules
Together we choose 2 to 3 key modules that prove the solution.
Build the working pilot
We build those modules as real, working software, free of charge.
You test it
Your team uses the pilot. The full project starts only after you approve it.
Start a conversation
Tell us how your business works.
Describe what is slowing your team down. We will help you work out what to build, and how a free pilot lets you judge our work before the full project.
Prefer WhatsApp? Start a chatWhat happens next
You send a short brief
The problem, the people involved and any target date. A senior engineer replies within 4 business hours.
We understand your workflow
A first call about how your business works today. An NDA can be signed before you share details.
You test a free pilot
You choose 2 to 3 key modules and we build them first, so you judge real software before the full project.