Service : automate
Paperwork, processed. All of it.
Document AI reads documents the way a trained operator would: extracting structured data from invoices, contracts, forms and reports, validating it against your rules and delivering it into your systems. Novistu builds document pipelines with accuracy targets, confidence scoring and human review where it counts.
The mechanism
Invoices, contracts, claims, forms, reports: read, extracted, validated and delivered into your systems, with confidence scores and review queues instead of rekeying.
- Receive
- Read
- Validate
- Review
- Deliver
The problem
What this fixes
Documents run your operations
Orders, invoices, claims, applications, contracts. Every one arrives differently and someone has to read it, type it and file it.
Templates break the moment reality changes
Classic OCR depends on fixed layouts. A new supplier, a new format, a scanned fax at midnight: the pipeline stalls and the backlog grows.
Errors are expensive downstream
A wrong figure in accounting, a missed clause in a contract, a typo in a claim. Extraction without validation just makes mistakes faster.
How we build it
Principles before code.
01
Handle any layout
Modern document models read structure and meaning, so a new layout is a variation, not a failure. Scans, photos and messy PDFs included.
02
Validate like an accountant
Extraction is checked against your business rules, reference data and arithmetic. Math must add up; IDs must match records; dates must make sense.
03
Confidence-based review
High-confidence fields flow straight through; anything uncertain lands in a review queue with the source highlighted. Reviewers teach the system by correcting it.
04
Deliver into your systems
Structured output goes to your ERP, accounting, CRM or database, with an audit trail for every field: source, confidence, who approved it.
Delivery
From first call to running system.
- 01
Sample
Analyse real document batches, define target fields, formats and accuracy bars.
1 week - 02
Build
Extraction, validation and review flow, measured against your sample set.
2 to 4 weeks - 03
Parallel run
System and team process the same batch; results are compared and tuned.
1 to 2 weeks - 04
Go live
Full volume with monitoring, review queues and accuracy reporting.
Ongoing
What you get
- Extraction pipeline for your document types
- Validation rules engine mapped to your business logic
- Review interface with confidence highlighting
- Delivery into ERP, accounting, CRM or databases
- Audit trail per field and document
- Accuracy and throughput reporting
Proof
Systems like this, in production.
Questions
Asked before every build.
On well-defined fields, modern models typically exceed human data-entry accuracy, and we prove it on your documents during the parallel run. The design goal is not perfection but economics: high-confidence automation with cheap human review of the remainder.
Printed text, scans and photos work well; handwriting depends on legibility. We test with your worst documents first, because that is where the pipeline will live.
Processed into your systems of record, with originals and extraction results stored where your compliance rules require: your cloud, your retention policy.
Processing can run entirely on open-weight models inside your infrastructure when required, and access is restricted per your policies. Nothing is shared across customers.
Tell us what is eating your team's hours.
A short brief, answered within one working day. The first call is free, and if AI is not the right answer, we will say so on that call.
First call free : honest about fit : no obligation