How it works
Document classification. A document arrives, the system understands what type it is and routes it to the right flow. No need for someone to open every attachment to decide where to put it.
Automatic matching. An invoice needs to be associated with the correct contract. AI reads the invoice, compares it with active contracts, suggests the most likely match. The operator confirms or corrects.
Semantic search. You have an archive of thousands of documents and need to find “that case where the customer asked for something similar to this”? Keyword search isn’t enough. Semantic search finds documents by meaning, not exact words.
Data extraction. A document contains structured information (dates, amounts, names) scattered in the text? AI extracts them and puts them in the right fields of your system.
We don’t build AI models from scratch. We use the best available models (OpenAI, Anthropic Claude, Google Gemini) and apply them to your data and processes.
We analyze the problem. Where do you lose time? Which activities are repetitive? Which errors are frequent? We identify where AI can have real impact.
We build the solution. We integrate AI models into your workflow. Not a separate application to open, but automation that works inside your systems.
We measure results. How many hours saved? How many errors avoided? AI must prove it works, it’s not enough to be “intelligent”.
How it’s built
Architecture
AI integrates via API into your existing systems. It can be a service called in real-time (classification on document arrival) or a nightly batch (daily invoice matching). For semantic search, we index documents with vector embeddings using a vector database.
Configurability
Model choice depends on the specific task: costs, latency, result quality. Configurable prompts and workflows to adapt to your specific processes. Automatic optimization to contain costs.
Available integrations
- OpenAI for text understanding and generation
- Anthropic Claude for complex document analysis
- Google Gemini for multimodal tasks
- Vector databases for semantic search
- Document systems for automatic classification
Audit and compliance
Sensitive data can be anonymized before sending to external models. For clients with strict requirements, we evaluate using on-premise or private cloud models. Complete traceability of processing and real-time cost monitoring.
Concrete use cases
Garnishment Management — Intelligent Document Extraction. In our third-party garnishment management system, AI completely automates document reading. It automatically processes documents from Sogert, Revenue Agency, debt collection companies. It extracts structured data: tax codes, IBANs (Italian and foreign), amounts, procedure IDs, garnished third parties. It handles complex formats like digitally signed PDFs (p7m), scans, non-standardized documents. It understands legal context using Spacy with Italian model to interpret abbreviations, synonyms, legal language. AI “understands” precept orders, notifications, revocations as an expert operator would, significantly reducing processing times and transcription errors.
Accounts Payable Management. In our accounts payable management system, AI automatically matches incoming invoices to existing contracts and orders and enables semantic searches in the document archive. Result: operators spend less time sorting invoices and more time handling exceptions.
See also
- InnovaNexus - AI for automatic invoice matching and expense control
- InnovaExpro - AI for automatic data extraction from legal documents