AI · Documents
AI for document processing and understanding.
The system reads a document, understands it and turns it into a structured record other systems can use.
The AI runs in a closed environment with no internet connection and uses only your documents.
When clients usually bring us in
- staff hunt for information across documents
- documents are reviewed by hand
- support answers the same questions repeatedly
- you need classification or data extraction
- you want AI inside the business process, not beside it
Your documents stay with you
We deploy document-processing AI in a closed environment with no connection to the internet. It works only with the documents and data we provide it, so your documents are never sent to public AI services or onto the internet.
What this means for you
- Less time spent looking for information.
- Less manual retyping of data.
- Faster processing of documents and requests.
- More consistent answers from your team.
- A clear trail of where each answer came from.
Problem → solution
Which documents we process
- contracts
- tender documentation
- invoices
- forms
- internal documents
- technical documentation
- letters and applications
What the AI does with a document
Reads and classifies
It recognises the document type and routes it into the right process.
Structures
It extracts the fields your systems need: parties, amounts, dates, references.
Compares and checks
It compares versions, checks against the template and flags deviations.
Finds what's missing
It flags missing data or attachments before the document moves on.
Summarises
It produces a summary highlighting risks and obligations.
Extracts deadlines and requirements
From tender or contract documents it extracts deadlines, conditions and requirements.
Use cases
Tender documentation
The system extracts conditions, deadlines and required references from a lengthy tender document.
Incoming invoices
Data is transferred to the accounting system without manual retyping.
Contracts
A review of obligations, deadlines and deviations from the standard template.
How we protect your documents
Contracts, invoices, and HR and business records often contain a company's most sensitive data. That is why security is part of the design from day one, not an afterthought.
- a closed environment with no internet connection
- the AI learns from and answers only on the basis of the documents and data we provide it
- documents are never sent to public AI services
- role-based access and a record of who reviewed or changed what
- low-confidence data is approved by a person before being transferred to the ERP or another system
A document's path through the system
Ingestion
the document arrives by email, through a form, from a folder or from the document management system
Reading
conversion to text; for scanned documents, using text recognition
Classification
what type of document it is and where it belongs
Extraction
reading the fields the business process requires
Validation
checking against existing data, rules and code lists
Structured record
the data in a form other systems can use
Routing
the document and the data are forwarded to the right person or system
Human review
borderline cases are sent for approval rather than having the system guess
Archiving
storage with metadata and an audit trail
Accuracy and borderline cases
No document-reading system is completely accurate, so what matters is what happens when the system is unsure. Correct design allows the system to show its uncertainty: the record is flagged and routed for review rather than having a value entered that would later need to be tracked down through the entire chain.
We measure accuracy on your documents, not on generic examples. That is why, before implementation, we need a sample of real documents, including badly scanned, incomplete or atypical examples.
What we need from the client
- a sample of real documents, including the more difficult ones
- the list of fields the process actually requires
- validation rules and code lists
- where the results go and who uses them
- agreement on who reviews the borderline cases
How we design the AI
Use case
We start by defining which decision or step the AI takes over, and where it must stop.
Data
We map sources, quality and access. Without organised data, AI cannot produce a dependable result.
Architecture
We choose the model, the retrieval approach and the point where AI plugs into the existing process.
RAG, agents, tools
The agent uses your systems through their APIs, within the permissions you define.
Keeping AI in control
Guardrails
What the AI may and may not do, when it must ask a person and when it stops the process.
Human in the loop
A person approves the sensitive steps. Each approval is logged together with the reason.
Evaluation
Regular checks on sample sets, so we notice when answer quality drifts.
Monitoring and cost
Tracking success rate, failures and cost per task, with alerts when something deviates.
Related work
FAQ
What about scanned documents?
We use OCR; the quality of the scanned document affects accuracy, so we always build in human confirmation for critical fields.
Which documents can AI process?
We process invoices, purchase orders, contracts, quotes, minutes and other documents from which data or answers need to be extracted.
Does a person still check the result?
Where a mistake is costly, yes. Low-confidence data is sent for approval before it goes into the ERP or another system.
Are our documents safe?
Yes. Document-processing AI runs in a closed environment with no internet connection, access is role-based and every review is logged. Documents are never sent to public AI services.
Does the AI learn from the internet?
No. The AI learns from and answers only on the basis of the documents and data we provide it, not from the internet.
Related reading
Tell us what you need
A few sentences are enough: what you need, for which process or system and by when. We will reply by email.
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Sounds like your project?
Send us the project description, your existing system, the tender documents or the event date.
Or email info@epix.si