Accounting

Parseo

AI-powered invoice digitization platform that extracts data from supplier invoices and pushes it directly into Lithuanian accounting software — automatically, from email to ledger.

Duration: 12 months

Team Size: 4 developers

Website

Overview

Parseo transforms invoice processing for Lithuanian businesses. Instead of manual data entry, accountants receive fully extracted and matched invoice data ready for one-click approval. The platform learns supplier-specific patterns — product names, warehouses, VAT codes — and applies them automatically. After ~100 invoices, most data auto-populates without human intervention.

The Challenge

Lithuanian accountants spend an average of 18 minutes manually entering each supplier invoice — reading PDFs, typing line items, matching products to catalogs, and pushing data into accounting software. With hundreds of invoices per month, this adds up to dozens of lost hours and inevitable human errors.

The Solution

We built Parseo, an end-to-end invoice digitization platform. Suppliers send invoices to a dedicated email address, Parseo extracts all fields using AI (PDF, scans, Excel, images), matches line items against product catalogs, and pushes validated data directly into Rivile, Finvalda, Centas, or Agnum via API. The system learns from every correction, reaching up to 99.5% accuracy.

Key Features

AI-Powered Data Extraction

Extracts structured data from PDF, scanned, Excel, and image invoices with up to 99.5% accuracy. Each field includes a confidence score — low-confidence data is flagged for human review before reaching the accounting system.

Email-to-Accounting Automation

Each client gets a dedicated email address. Suppliers send invoices directly — no portal, no changes to their workflow. Parseo processes attachments automatically and routes extracted data to the accounting system.

Supplier-Specific Learning

The system learns from every correction. Product names, warehouses, VAT codes, and accounting fields are remembered per supplier. After ~100 invoices, the majority of fields auto-populate without human intervention.

Intelligent Matching Rules

Automatic product catalog matching with semantic understanding — even when supplier product names differ from accounting system entries. Users can save corrections as reusable rules that apply to all future invoices.

Technical Details

Architecture

Domain-Driven Design architecture built with NestJS and TypeScript. Multi-tenant system with complete data isolation. Direct API integrations with Rivile GAMA, Finvalda, Centas, and Agnum accounting platforms.

Deployment

Containerized deployment on EU servers with PostgreSQL, Redis, and AWS S3 for document storage. GDPR compliant with encrypted connections and automated backups.

Security

Role-based access control with team management, API key authentication, comprehensive audit trails, and full processing history. Every extraction includes confidence scores for human review.

Performance

Asynchronous job processing with BullMQ and Redis. Handles PDF, scanned documents, Excel, and image invoices. Supplier-specific learning model improves accuracy with each processed document.

Project Timeline

4 weeks

Architecture & Foundation

Domain-driven design planning, NestJS architecture setup, database schema design, authentication system, and core infrastructure with Docker containerization.

8 weeks