Documents in.Clean data out.In 5 seconds.

The 15th of the month, Friday 5pm, the accounting team of your industrial SMB. An intern is retyping the 412th invoice of the month into the ERP, net amount, VAT, supplier ID, due date, looking back and forth between the PDF and the screen. She mistypes the tax ID of a foreign supplier: 0.7% data-entry error rate on average for the year. Three months from now, the tax audit will catch that line and your CFO will spend a full week reconstructing the trail. It's not the intern's work that's the problem, it's that you're paying someone in 2026 to do what an LLM does in 5 seconds with 99% accuracy.

IDC measured that processing one invoice manually costs an average of 17 dollars (entry, validation, archiving, error hunting), versus 0.40 dollars for an invoice handled by smart OCR. Goldman Sachs estimates AI document automation will free up 2.3 million FTEs in finance and back-office by 2028. Forrester predicts 90% of B2B companies will abandon template-based OCR by 2027 in favor of LLM extraction, because templates don't scale to the 1,000+ suppliers of a modern scale-up.

Wikolabs installs AI systems built on open-source models, on your premises, paid once. No black box: your data, your prompts and your history stay in your infrastructure. We quote at a fixed price or on time and materials, never per ticket or per token, and we say before you sign what works and what does not yet.

Concretely: you drop the document via UI or REST API. DocExtract OCRs it, even skewed or damaged scans, then an LLM understands the context and extracts each field with no template. Built-in business rules for tax IDs, IBAN, VAT, amounts and dates: every field is validated before delivery to your ERP or CRM via webhook. 5 seconds per document, 99% accuracy, zero templates to maintain. Your intern can finally do real work.