Artificial intelligence
Computer Vision, OCR and Document AI
Structured data out of images and scans: invoices, acts, plate numbers, counts.
- ID
- AI-06
- Rollout stages
- 05
The business problem
Invoices, delivery notes and identity documents are still typed into the system by hand. It is slow, error-prone, and at month-end the volume doubles or triples. Bookkeeping falls behind and the mistakes only surface during reconciliation.
What we build
A photo or scan enters the pipeline: text is recognised, fields are extracted — date, total, tax ID, line items — and the result is written into the accounting system. Fields the system is unsure about are flagged, and the operator checks only those rather than re-reading the whole document. In industrial settings the same pipeline drives counting from camera feeds, plate recognition and quality checks.
Rollout stages
- 01
Audit and analysis
We collect the document types and assess how varied the quality and formats are.
- 02
Architecture and design
We agree the fields to extract, the accuracy target and the uncertainty threshold.
- 03
Development
We build the recognition pipeline and the operator review interface.
- 04
Integration
We wire up writing into the accounting system and set the reconciliation rules.
- 05
Full rollout
We move to the full document stream and start tracking accuracy statistics.
What the client gets
- Automatic field extraction from documents, written into accounting
- Only the uncertain fields reach an operator for review
- Recognition of Azerbaijani, Russian and English documents
- Camera-based counting and plate recognition for industrial use
Possible integrations
- 1C
- SAP
- Odoo
- PostgreSQL
- S3-compatible storage
- RTSP camera streams
Security approach
Where identity documents are processed, retention of the original images is limited and the files sit in encrypted storage. Processing can run entirely inside your own infrastructure — in which case no document leaves the company.
Ongoing support
New document layouts are added and recognition accuracy is tracked. When a supplier changes their form, the system is retrained on it.
Related services
- AI-02
Private & Local AI
The model runs on your server; documents never leave the company network.
- SW-05
Accounting and Financial Systems
Ledger, reconciliation, payment calendar and management reporting — from one source.
- DI-04
Retail, Manufacturing and IoT
Equipment, till and sensor data — at the moment it happens, not in next week’s report.
Consultation on this practice
Describe your situation briefly — we will outline the options and the first step.