New document types took weeks of manual coding. GenAI cut setup to minutes, letting teams refine extractions via natural language.
An intelligent document processing provider enables organizations globally to automate information extraction from high volumes of physical documents.
Reliance on traditional machine learning models required extensive technical setup and manual data annotation for every new document type. Even with...
“We used open-source models that we fine-tuned for specific document types and schemas, and it took a lot of engineering effort to do that. Even when we eventually created a self-service model for our customers, they still needed to produce their own training data sets.”
AI platform for automated data extraction and intelligent document processing.
Cloud computing platform and on-demand infrastructure services.
Related implementations across industries and use cases
Manual reviews of foreign engineering docs slowed consultants. GenAI now summarizes key points, cutting reporting time by 75%.
Legacy OCR forced manual checks on 40% of invoices. Claude now interprets diverse layouts without static templates.
Malformed PDFs forced engineers to manually patch pipelines. AI agents now parse complex files into clean markdown, ending manual fixes.
Engineers manually correlated alerts across systems. AI agents now diagnose issues and suggest fixes, cutting recovery time by 35%.
Minor edits required days of crew coordination. Now, staff use avatars to modify dialogue and translate languages instantly.
Lab supply orders were handwritten in notebooks. Digital ordering now takes seconds, saving 30,000 hours for research annually.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.