Extraction pipelines + semantic knowledge search, in production.
We build AI that reads, extracts, and understands your documents — then lets your team ask questions in plain language and get answers with the source, right inside the tools they already use.
AI Document Processing & Knowledge Search
Documents pile up faster than anyone can read them, and the answers your team needs are locked inside files no one can search.
Answers live in PDFs, wikis, tickets, and email — nobody can find them fast.
Teams retype invoices, forms, and records by hand. Slow, costly, error-prone.
Ctrl+F and legacy search miss anything not worded exactly right.
Two people get two answers. Neither can prove which is correct.
Two connected systems — a document processing pipeline that structures your files, and a knowledge search layer that makes them instantly answerable.
Pull structured data from invoices, contracts, forms, and records — OCR + LLM parsing that reads even messy scans.
Every incoming document is identified, tagged, and filed automatically — no manual sorting.
Ask questions in plain language across your entire document base and get answers, not just links.
Long contracts and reports distilled into the answer you need — with the exact clause it came from.
End-to-end pipelines that ingest, process, validate, and route documents into your existing systems.
A chat assistant grounded in your knowledge base — answering staff and customers with your own content.
Every document that enters your business runs a controlled path — parsed, structured, indexed, and made answerable — with validation at each step.
01
Documents flow in — upload, email, API, or a watched folder in your DMS.
02
OCR + LLM parse text, tables, and fields, even from scans and handwriting.
03
Data is classified, validated against your rules, and normalized.
04
Content is embedded into a vector store for meaning-based retrieval.
A user asks “How long do I have to send something back?” — keyword search finds nothing because the contract says “return window.” Semantic search understands they mean the same thing.
Contracts, records, and financials demand more than a demo. Governance is engineered into the pipeline.
Documents are processed in your tenant or private cloud — never used to train public models.
Sensitive fields identified and masked before anything reaches an external model.
Search respects your access controls — users only see what their role permits.
Every query, answer, and source access logged and traceable.
Self-hosted models and vector stores where data cannot leave your infrastructure.
Answers are generated from your documents with citations — no hallucinated facts.
Contract review, clause search, obligation tracking
Invoice extraction, statement parsing, reconciliation
Records summarization, intake forms, prior-auth
Policy Q&A, onboarding docs, SOP search
Claims documents, policy lookup, form extraction
Knowledge-base answers, ticket deflection
FAQ’s
PDFs (including scans), Word, Excel, images, emails, and more — 20+ formats. OCR handles scanned and even handwritten documents; LLM parsing extracts tables, fields, and line items.
Keyword search matches exact words. Semantic search understands meaning — so “how long to send something back” finds a clause about “return window.” Answers come with the exact source citation.
Answers are generated only from your documents and always cite the source. If the answer isn’t in your content, the system says so rather than inventing one.
Yes. It ingests from your DMS, drives, email, or APIs, and pushes structured data into your ERP, CRM, or database. Search embeds inside the tools your team already uses.
Processing runs in your tenant or private cloud, PII is detected and redacted before any external model call, answers respect your access controls, and everything is audit-logged. ISO 27001 certified.
Yes. For regulated data we deploy self-hosted models and vector stores on your infrastructure so documents never leave your environment.
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