Buried PDF Information
Your business runs on contracts, technical manuals, compliance policies, and reports. They are stored across SharePoint, email, and shared drives. Nobody can find what they need quickly, and knowledge is buried in PDFs.
Unlock the knowledge trapped inside your PDFs, contracts, manuals, and reports. We build secure, citation-backed RAG (Retrieval-Augmented Generation) pipelines that let your team get accurate answers in seconds.
No commitment No sales deck Response within 4 hours
Traditional search tools return documents, not answers. Generic AI tools make up answers because they haven't read your files.
Your business runs on contracts, technical manuals, compliance policies, and reports. They are stored across SharePoint, email, and shared drives. Nobody can find what they need quickly, and knowledge is buried in PDFs.
Generic AI tools give confident answers based on nothing, because they lack access to your actual files. Search tools index files but don't synthesize answers, returning documents instead of cited answers.
Documents are chunked, converted to vector embeddings, and indexed securely.
The system retrieves the most relevant passages from your actual content and uses an LLM to synthesize cited, accurate answers without guessing.
We engineer RAG pipelines for specific data sources, query behaviors, and sovereignty demands.
Ask questions of your library in plain English. Runs privately in your secure cloud environment.
Extract terms, obligs, dates, and non-standard clauses. Compare agreements against templates.
Give staff a way to query compliance procedures. Returns the exact policy section in seconds.
Make technical guides searchable by symptoms or components, returning exact page numbers.
Extract structured data from unstructured invoices or forms. Output to databases or ERPs.
We don't use off-the-shelf wrappers. We build custom RAG pipelines optimized for precision.
Connect PDF, Word, Excel, email, HTML, SharePoint, and custom databases.
Semantic, paragraph, or sliding window partitioning matching your document layout.
Azure OpenAI, OpenAI, or local open-source models for data compliance.
Hybrid vector search, metadata filtering, and semantic re-ranking (Cohere).
Transparent, milestone-based tiers matching the size of your document corpus.
One document type, one use case, deployed in a sandbox. Answers whether RAG works for your queries.
Full production deployment. Multiple document sources, ingestion pipeline, re-ranking, API/UI, and monitoring logs.
Post-deployment maintenance: document updates, model upgrades, prompt tuning, and performance audits.
Stop searching. Start finding. Contact our RAG architects to scope a secure sandbox pilot.