Manual data entry
A clerk receives a pile of documents, types fields into a system, hours every day. High labor cost, a workday that can't be accelerated.
Automatic document processing · in production
AI Documents
Any business document that needs to be typed manually - invoices, contracts, certificates, licenses, forms. The agent extracts data automatically, cites the source, and reports confidence level. What used to take hours takes seconds.
Why it hurts
The hidden cost of manual data entry
Organizations that feel this burden usually don't see it as a separate budget line. It's hidden in clerk work, in delayed approvals, and in customers who wait.
Accumulated typing errors
Wrong date, wrong number, off by one amount - one error in every hundred records, but billing doesn't fix itself.
Bottleneck
Documents pile up in boxes. When the clerk is sick or on vacation, the flow stops. Customers wait for approvals, projects are delayed.
What the agent does
Three capabilities, no more
Not a chatbot, not a general assistant. The agent does one thing well: receives a document, returns structured data. With full transparency.
Automatic extraction
Upload a PDF or photo, the agent identifies the document type and returns structured JSON with all relevant fields. In seconds.
Source citation for every value
Every field comes with the exact quote from the document. You can verify with a click - where exactly the agent found that number.
Confidence score per field
The agent knows what it's uncertain about. Fields with a low score are automatically routed to manual review - nothing goes out blindly.
Who it's relevant for
Firms, companies, organizations
As a rule - if there's a document you need to type from into a system, the agent can do it. Below are industries where I've already identified a good fit.
Transport & distribution companies
Vehicle licenses, insurance policies, maintenance invoices, inspection reports. The agent runs in production in a logistics system and handles automation across hundreds of documents per month.
Accountants & bookkeeping firms
Supplier invoices, receipts, payslips, bank statements. Fields: business ID, amount, VAT, date, account classification. Instead of hiring data-entry staff during tax season.
Law firms
Contracts, judgments, client documents, certificates. Extraction of parties, material clauses, dates, obligations, closing dates. Your clients get an answer the same day, not a week later.
Financial & insurance institutions
Application forms, ID documents, income certificates, policies. Accelerated KYC, faster account opening, underwriting processes that don't depend on clerk availability.
Human Resources
CVs, certificates, employment verifications. Classification, relevant experience extraction, comparison against job requirements. Screening hundreds of candidates turns into minutes.
Any organization with manual data entry
If you have a clerk typing data from documents for hours a day - there's an opportunity here. Worth a call to examine the numbers: agent cost vs. current staff cost.
Why trust it
Zero hallucinations. Full transparency.
AI that can't be verified shouldn't be used for work with business significance. The agent is built so every value it returns can be manually verified in seconds.
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No hallucinations
When the document is unreadable, the agent returns 'unreadable' instead of guessing. Accountability is yours, judgment is yours.
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Every value is verifiable
Exact source citation from the document. You can verify it yourself with a click - not a black box.
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Manual review for low-confidence
Values the agent is uncertain about automatically enter a manual review queue. Not dangerous - a defined process.
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In production today
The agent runs in production in a commercial logistics system, processing vehicle documents across all categories: licensing, insurance, inspection, maintenance. Not a theoretical claim.
production case study
Vehicle documents in a commercial logistics system
In a logistics system I operate - a company with a fleet of trucks and vans - the agent automatically processes all fleet documents: vehicle licenses, insurance policies, annual inspection reports, maintenance invoices. Expiry dates were identified, amounts recorded for billing, alerts triggered 30 days in advance. One person supervised a process that previously required a full-time clerk. The agent isn't an experiment - it's in production.
How to get started
Implementation process
- 01
Intro call
Which documents, at what volume, into which system. No commitment, no deck.
- 02
POC on your own samples
We'll build a custom field definition, run it on 20–50 real documents, and review the results together.
- 03
Integration
Simple API - send PDF/JPEG, receive JSON. Can connect to any existing system.
- 04
Production
Performance monitoring, prompt tuning based on edge cases, continuous improvement. Not a system that gets installed and disappears.
Do you have a document stream that needs data extracted?
A half-hour call is enough to understand if this fits. I'd be happy to show the agent in action on a real example from your domain.
Let's talk