Morphik automates the end‑to‑end workflow for enterprise‑grade document intelligence. It ingests PDFs, images, and schematics natively; embeds whole pages; builds a semantic knowledge graph; and serves accurate answers via UI, SDK, or REST API no duct‑taped pipelines and with accuracy outpacing GPT‑4 on technical retrieval benchmarks.
Key Features:
- Visual‑first ingestion & indexing – embeds full pages (images + text), not just OCR, preserving spatial and visual context for reliable RAG.
- Knowledge Graph & GraphRAG engine – automatically builds semantic graphs from your documents, enabling cross‑page, multi‑hop query reasoning.
- High accuracy & low latency – achieves ~96 % accuracy on arXiv QA benchmarks with 200 ms retrieval response at scale.
- Developer‑friendly APIs & UI – ingest, query, and explore via REST API, Python SDK, or embeddable web console; integrates into any app stack.
- Enterprise‑grade governance built‑in – supports roles-based access control, natural‑language rules, multi‑tenant isolation, and on‑prem/cloud deployment models.
Use Cases
- Engineering, aerospace & research teams needing precise retrieval across papers, technical diagrams, and specs.
- Legal and compliance teams building document search over contracts, citations, and scan-heavy archives.
- Healthcare and pharma firms analyzing diagnostics, patents, trial data, and clinical literature.
- Internal enterprise chat agents answering queries by reasoning over visual and tabular policy docs or training manuals.
- Analytics platforms & internal R&D tools that extract structured knowledge from inconsistent, multimodal sources with automation.
