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Classifies documents and extracts text, tables, images, and fields from scans, faxes, PDFs, forms, and Office files, combining ICR, layout understanding, and NLP, delivered through Enterprise h2oGPTe.
Template OCR breaks when the form changes, and RPA memorizes one layout. Document AI learns the document class and generalizes, then hands the result to a model, an agent, or an application.
Document AI lives inside Enterprise h2oGPTe, fed by the open-weight Mississippi vision-language models. Highlighted are h2oGPTe, the open models, and the document sources.
Most agent plans in a regulated business start with a document: a claim, a loan packet, an invoice, a referral. Document AI inside h2oGPTe turns it into structured data, and the H2O AI Super Agent takes it from there: validate, route, update, escalate, every step logged.
Same platform either way: the same capabilities, the same governance, and the same audit trail. The choice stays open, so you can switch between them as the business changes, without rebuilding what runs on top.
We will ingest them into h2oGPTe, extract the fields, and hand the result to an agent that routes them, in one session.
The H2O AI Cloud for Government has achieved FedRAMP High Certification, delivering the highest standard of cloud security so federal agencies can harness predictive and generative AI without compromising data sovereignty or compliance.
Yes. Document AI capabilities are surfaced through Enterprise h2oGPTe: ingest documents into a collection, OCR and layout run on Mississippi vision-language models, extract fields and tables, ask questions with Agentic RAG citations, and hand structured data to the H2O AI Super Agent.
