Document AI — Intelligent Document Processing.
Extract, classify, and act on data locked in your documents — automatically, accurately, in seconds instead of hours.
Book a Free Document AI ConsultationEvery organization drowns in documents.
Contracts, invoices, purchase orders, intake forms, compliance reports. Manually reading, extracting, and routing this information is slow, error-prone, and expensive — and it scales badly as your organization grows.
Document AI automates the entire pipeline: ingest a document, extract the key data, validate it, and push it to the right system — automatically. Your team handles exceptions, not routine processing.
We are a Canadian consulting and AI automation firm based in Ancaster, Ontario. Every engagement ends with a working process in your environment, not a report.
Quick facts
From document intake to data in your systems.
What AI document processing automates
Most firms do not have a document problem. They have a re-keying problem.
Invoices and accounts payable
Receipts and expense claims
Contracts
Purchase orders
Forms and applications
Onboarding and HR documents
Emails with attachments
How automated document processing works, step by step
Every document processing automation we build follows six stages.
Intake
Documents are collected where they already arrive, such as a shared mailbox.
Classify
Each document is identified by type (invoice, contract, form) so it follows the right rules.
Extract
Fields are read by meaning, not position, and each value carries a confidence score.
Validate
Values are checked against your rules: vendor, PO match, duplicates.
Human review of exceptions
Low-confidence or failed items go to a review queue, document and values side by side.
Push into your systems
Validated data is written into your ERP, accounting system or SharePoint, with every step logged.
The review step is what lets a finance team trust the output from week one.
OCR vs intelligent document processing vs AI document automation
Three terms, three levels of capability.
| OCR | Intelligent document processing (IDP) | AI document automation | |
|---|---|---|---|
| What it does | Turns images of text into characters | Classifies documents and extracts named fields | IDP plus validation, routing and posting into your systems |
| New layouts | Poorly; needs templates | Generally yes, within a document type | Yes, and routes the unfamiliar to a person |
| Human role | Checks and re-keys | Reviews fields, then does the next step | Handles exceptions only |
Extraction alone still leaves someone moving the data. Rule-based screen work pairs well with robotic process automation (RPA); work needing judgment across systems pairs with AI agents. See RPA vs AI agents.
Document & Invoice Automation Package
Automate your highest-volume document type end to end, usually supplier invoices, and prove it on your own documents.
What is included
- Discovery of your workflow, volumes and exceptions
- Classification and extraction for one priority document type, tested on your documents
- Validation rules agreed with your team
- An exception review queue with thresholds you control
- Integration into one system: ERP, accounting platform or SharePoint
- A full audit trail of every document and correction
- Testing, training, a run-book and 30 days of support
What AI document automation costs and how long it takes
Every project is a fixed fee, not hourly, with a proposal within 48 hours of a free 30-minute call. If the work runs long, that risk is ours. Four things drive the fee:
- Volume. Documents per month, and month-end peaks.
- Variety. One standard form is simpler than invoices from hundreds of suppliers.
- Integrations. One destination system is simpler than an ERP, SharePoint and a CRM at once.
- Accuracy and control. Tighter validation and approval tiers take more design and testing.
One document type into one system typically takes 4–6 weeks. Formal procurement can add 1–2 weeks before we start. Microsoft usage charges are separate; we size them during discovery.
Tools we build AI-powered document processing on
We build on Microsoft tools you likely already own.
Who intelligent document automation suits
Small and mid-sized organizations where the same documents arrive every week and someone retypes them.
Accounting and bookkeeping
Professional services
Construction
Manufacturing
Healthcare clinic administration
Property management
Handling a handful of documents a week? A good template will serve you better, and we will say so.
Ready to stop processing documents manually?
Book a free consultation — we’ll map your document workflows and show you exactly what can be automated.
Book a Free Document AI ConsultationDocument automation questions, answered
What does it mean to automate document processing?
To automate document processing is to replace the manual steps between a document arriving and its data landing in your systems. Instead of a person opening a PDF, reading it, and keying values into an ERP or finance system, the document is classified by type, the required fields are extracted, the values are validated against your own business rules, and the result is written into the destination system. A person stays in the loop for exceptions and approvals.
The practical test of whether a process is a candidate: the document arrives in a predictable way, the same fields are needed every time, and somebody is currently retyping them.
What is AI document automation, and how is it different from OCR?
Traditional OCR converts an image into characters. It does not know what those characters mean, so it depends on fixed templates and breaks when a supplier changes their invoice layout. AI document automation adds a comprehension layer: the model identifies the document type, locates the fields by meaning rather than by coordinates, and handles layouts it has not seen before.
The difference matters most where documents are variable — contracts, supplier invoices from many vendors, claim forms, and anything arriving as a scan or a photo.
Which documents are worth automating first?
We start where volume and structure intersect. In most organisations that means:
- Invoices — high volume, consistent fields, direct finance impact
- Purchase orders and order confirmations — straightforward matching logic
- Contracts — extracting dates, parties, renewal and obligation clauses
- Forms and applications — onboarding, claims, and intake
- Delivery notes and receiving documents — three-way match completion
We deliberately do not start with your most complex document type. The first build exists to prove the pipeline end to end.
How does document AI connect to our ERP or SharePoint?
Extraction is only half the job — the value appears when data reaches the system of record. We integrate with the destination you already run, typically SharePoint, Microsoft 365, or an ERP, using its supported interfaces rather than screen-scraping. ERP document automation generally means writing validated field data into the ERP transaction, attaching the source file for audit, and routing anything that fails validation to a named human.
What accuracy should we expect, and what happens when it is wrong?
Accuracy depends on document quality, layout variability and how tightly your validation rules are written, so we establish it on your own documents during discovery rather than quoting a figure up front. The more important design question is what happens to the uncertain cases. Every workflow we build carries a confidence threshold: items above it flow through, items below it go to a review queue with the extracted values and the source document side by side.
Automating 100% of documents is rarely the goal. Automating the predictable majority, and routing the rest to a person quickly, is.
Do we need to replace our current document systems?
No. The automation layer sits on top of what you already have. If documents arrive by email and live in SharePoint, that stays true — what changes is the manual handling in between. We would rather integrate with a system that works than add a migration to the project.
How much does AI document processing cost?
It depends on volume, document variety, the systems involved and how much validation you need, so we do not publish a flat rate. Every project is a fixed fee: after a free 30-minute call, you get a proposal with one price, scope and timeline within 48 hours.
How long does it take to automate document processing?
Typically 4–6 weeks for one document type into one system, covering discovery, build, testing on your documents, training and go-live. Formal procurement can add 1–2 weeks before the start.
How do you keep our documents secure, and can they stay in Canada?
Wherever possible we build inside your own Microsoft 365 and Azure tenant, so documents stay under your existing access controls, retention and audit logs. Azure has Canadian regions (Canada Central and Canada East); where you need Canadian data residency, we deploy there wherever the specific service is offered, and confirm it during discovery.
What volume of documents makes automation worth it?
There is no single threshold. Add up the hours spent each month reading and retyping one document type, plus the cost of errors and late approvals. A steady weekly flow is the strongest case; high-stakes contracts can justify it too. If the numbers do not stack up, we will say so.