AI Product Development
Stop typing data from documents into your systems
We build systems that read your incoming documents, pull out the fields you need, check them and send them to the right place, with people reviewing the uncertain ones.
The problem
The problem this solves
Documents still drive a lot of business: invoices, purchase orders, delivery notes, application forms, bank statements, contracts, identity documents. In most companies, someone opens each one and types the important details into another system. It is slow, boring and error-prone, and the backlog grows every time volume rises.
Older tools helped only a little. Template-based extraction broke whenever a supplier changed their layout. Basic OCR turned images into text but did not understand which number was the total and which was the tax.
Modern AI changes this. A multimodal model can read a document the way a person does, understand its layout and return the fields you need as structured output, even from layouts it has never seen. Combined with validation rules, such as checking that line items add up to the total or that a supplier exists, it becomes a reliable pipeline.
No extraction is perfect, so we design for exceptions. Each field gets a confidence score. Documents that pass every check go straight through. Anything uncertain goes to a review screen where a person sees the document and the extracted fields side by side and fixes them in seconds. Every correction improves the system.
This service powers several of our solutions, including invoice processing, contract review and receipt processing.
We also plan for the documents themselves. Originals are stored securely with their extracted data, retention rules match your legal requirements, and every change a reviewer makes is logged. When an auditor asks where a number came from, you can show the source document in one click.
What you get
What you get
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Document intake
Documents collected from email, uploads, scanners or shared folders automatically.
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AI extraction
Fields, tables and line items pulled out of any layout into a consistent format.
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Validation rules
Totals, dates, IDs and reference data checked before anything is saved.
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Confidence scoring
Each field scored so uncertain values are flagged instead of trusted.
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Review screen
Document and extracted data side by side, with quick correction for reviewers.
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System integration
Verified data sent to your ERP, accounting, CRM or database.
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Searchable archive
Every document stored with its extracted data, searchable later.
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Accuracy reporting
Straight-through rates, correction rates and processing times tracked.
How we build it
How we build it
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1
Collect samples
We gather a realistic set of your documents, including messy ones.
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2
Define fields and rules
We agree what to extract and how to validate each field.
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3
Prototype
Extraction tested on your samples with accuracy measured per field.
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4
Build the pipeline
Intake, extraction, validation, review screen and integrations built.
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5
Run in parallel
The system runs alongside manual entry until accuracy is proven.
AI and people
Where AI helps, where people decide
AI makes the repetitive parts faster. The decisions that shape your product stay with experienced people.
Where AI speeds things up
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Reading documents and extracting fields in any layout.
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Classifying document types automatically.
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Generating validation rules from sample data.
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Producing test sets from real documents.
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Highlighting patterns in corrected fields.
Where people decide
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Which fields matter and how they are validated.
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The confidence level that allows straight-through processing.
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How exceptions are reviewed and by whom.
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Where data may be stored and processed.
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When the system can replace manual entry.
Is this right for you?
When this is the right choice
A good fit when
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Staff type data from documents into systems every day.
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Documents come in many layouts from many senders.
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Errors in that data cost time or money later.
Consider something else when
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You receive only a few documents a month.
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Senders can send structured data directly through an integration instead.
Timeline and cost
What affects the timeline and cost
A prototype on one document type usually takes a couple of weeks. A production pipeline with review screens and integrations takes longer, and we run it in parallel with manual work before switching over.
We do not publish fixed prices because scope drives cost. How we estimate.
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Document types
Each type needs its own fields, rules and testing.
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Document quality
Poor scans and handwriting need more processing and review.
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Validation depth
Checks against external systems add integration work.
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Target systems
Each destination system needs a tested connection.
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Volume
Processing costs scale with the number of pages.
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Data sensitivity
Identity and financial documents need stricter handling.
Keep exploring
Related services, solutions and reading
Related services
View all related services- AI Product Development AI agents, knowledge assistants, copilots and document automation built into the way your team already works.
- Computer vision Software that reads photos and scans: damage checks, stock counts, document capture and quality control.
- Customer portals A secure place where your customers upload documents, check status, pay and message your team.
- RAG knowledge assistants Assistants that answer questions from your own documents and show where each answer came from.
- Billing and payments Checkout, invoices, subscriptions, refunds and the accounting exports your finance team needs.
- AI workflows Step-by-step automations where AI handles the reading, sorting and drafting inside a process you control.
Solutions
View all solutions- AI document processing Read forms, applications, IDs and statements, extract the fields you need and route each document for the right review.
- Invoice processing Read supplier invoices, match them to orders and push approved ones into accounting, with exceptions flagged for review.
- Contract review assistant Highlight unusual clauses, missing terms and deviations from your standard positions, so reviewers focus where it matters.
- Receipt capture and matching Snap a receipt, and the details are read, categorized and matched to the card transaction and the right project.
- Automated quoting Draft accurate quotes and proposals from a request, your price rules and past work, for a person to approve.
- Screening assistant Summarize each application against your criteria, flag strong matches and missing information, and leave every decision to a person.
Industries
View all industries- Finance and accounting Client portals, document collection, invoice and receipt processing, and reporting for accounting firms and finance teams.
- Insurance Claims intake, document and photo processing, policy knowledge assistants and customer portals for brokers and insurers.
- Legal Contract review assistants, knowledge search, intake and document automation for law firms and in-house legal teams.
- Tax and compliance services Client portals, document checklists, case queues and deadline tracking for tax preparers and compliance firms.
- Recruiting and staffing Candidate screening assistants, ATS integrations, interview notes and onboarding automation for recruiters and staffing firms.
- Construction and facilities Job tracking, maintenance requests, inspections, quotes and proof-of-work photos for builders and facility teams.
Case studies
View all case studies- Payroll system for an IT services company Payroll is calculated from recorded inputs, reviewed once and sent as payslips in a single batch, with every change logged.
- Tax filing service platform Clients upload documents and see where their case stands, and staff work from one queue with deadlines and reminders.
Guides and articles
View all guides and articlesAI models
View all ai models- Vision and multimodal Models that read images, scans, screenshots and sometimes audio or video alongside text.
- Gemini 3.8 Flash Google's most capable Flash model, stable since September 2026, for agents, software engineering and enterprise workflows with full multimodal input.
- Gemini 3.5 Flash-Lite Google's lowest-cost current Gemini model for high-throughput work such as sub-agent tasks and document parsing.
- Mistral OCR 4.1 Mistral's document OCR model, turning pages into structured output with bounding boxes, block labels and confidence scores.
- Gemini 3.1 Pro Google's most advanced Gemini model for reasoning, software engineering and agent work, reading text, images, audio, video and PDFs. Available as a preview.
- Claude Sonnet 5 Anthropic's balance of speed and intelligence: a strong everyday model for assistants, document work, tool calling and coding.
MCP servers
View all mcp servers- Files and storage Servers that connect AI to cloud drives and object storage, so it can find, read and organize documents.
- Box Box's official MCP server lets AI search and read files, ask questions across documents with Box AI, extract data and upload files.
- Dropbox Dropbox's own MCP server lets AI list, search and read files, convert them to markdown and create, move, share and delete files. In beta.
- AWS S3 Amazon S3 is handled through the managed AWS MCP Server, which lets AI run scripted AWS actions, create presigned links and search AWS docs.
- Google Drive Google's own Drive MCP server lets AI search, read and create files in Google Drive, with your Google Workspace sign-in.
- OneDrive Microsoft's OneDrive MCP server, part of its Work IQ preview, lets AI find, read, create, move, share and delete files in OneDrive.
Glossary terms
View all glossary terms- OCR OCR, or optical character recognition, is technology that turns text in images and scanned documents into machine-readable text.
- Structured output Structured output is when an AI model returns its answer in a fixed format, such as JSON matching a schema, so software can use it reliably.
- Multimodal model A multimodal model is an AI model that can take in more than one kind of input, such as text with images, audio or video.
- Context window A context window is the maximum amount of text, measured in tokens, that an AI model can consider at once, including the question, documents and its answer.
- JSON JSON is a simple text format for structured data, made of names and values, that most software and APIs use to exchange information.
- LLM integration LLM integration is connecting a large language model to your software and data, so AI features work inside your own products and processes.
FAQ
Questions about document automation
Have a question that is not here? Ask us directly.
It depends on document quality and complexity. Clean, typed documents usually extract very reliably. We measure accuracy on your own samples and route uncertain fields to review, so errors are caught rather than saved.
Often yes, for clear handwriting, but accuracy is lower than for typed text. We test on your samples and set review thresholds accordingly.
No. Modern AI models understand layouts they have not seen before, so new suppliers do not need setup. Validation rules still catch mistakes.
We choose providers and regions that match your data rules, and can use self-hosted models when documents must stay on your servers. See AI document processing.