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Česky
Turn invoices, contracts, RFPs, and forms into clean structured data your systems can act on. OCR plus modern multimodal models, wrapped in a pipeline with confidence scoring, schema validation, and a human-review queue for the rows that need a second pair of eyes.
Start a projectMost enterprise documents weren't designed to be parsed. Scanned PDFs, multi-page forms, vendor templates that change every quarter, tables that wrap across pages, handwritten notes in the margins. We build extraction pipelines that handle the documents you actually have — not the clean samples in the demo deck.
Supplier invoices — line items, VAT, due dates, PO references — straight into your AP system.
Multi-page contracts — parties, terms, renewal dates, governing law, indemnity clauses.
Inbound RFPs and tenders — requirements, deadlines, attachments, compliance checklists.
Onboarding forms and KYC packets — identity fields, signatures, attached evidence.
We start from the target schema in your downstream system — ERP, AP, CRM, data warehouse. The pipeline returns data in exactly that shape, validated, ready to write.
Layout-aware OCR for scans and photos, multimodal models (Claude, GPT, Gemini) for documents where structure carries meaning. We pick per document type, not per vendor.
Every extracted field carries a confidence score the pipeline can act on — auto-approve, flag for review, or reject. Thresholds are tuned per field, not per document.
A review UI where your team checks low-confidence rows side-by-side with the source page. Corrections feed back into evaluation so the pipeline learns where it's weak.
Every field traces back to a page, region, and model call. PII handling, retention rules, and data residency wired in from day one — not bolted on for the audit.
Pipelines land where your work already happens — SAP, Microsoft Dynamics, Helios, custom ERPs, SharePoint, message queues, REST APIs. No new tool for your team to log into.
Classic OCR gives you a stream of characters. That's the easy 20%. The hard 80% is everything after: deciding which number on the invoice is the total versus the subtotal versus the VAT base, knowing that "Acme s.r.o." and "ACME spol. s r.o." are the same supplier, telling a hand-written tick from a coffee stain.
That's where modern multimodal models earn their keep — they read the document the way a person does, with the layout, the headings, and the surrounding context. We combine them with OCR, schema validation, and your own master data so the output is defensible, not just plausible.
We start by reading a real sample of your documents — not the clean ones, the awkward ones. We define the target schema with your team, set acceptance thresholds per field, and ship a pipeline that runs in your environment (Azure, on-prem, or hybrid). Evaluation harnesses come standard.
We stay long enough to hand over operations — runbooks, dashboards, retraining playbook. Not a Jupyter notebook on a laptop. Not a perpetual support contract.