Hybrid RAG Solution
RAGFORGE
AI that answers from your own documents
Vector search alone misses exact values like employee IDs or clause numbers. RAGFORGE runs semantic search, keyword search, and document structure and metadata search together, then merges the results. Every answer carries its source passage, and anything absent from the documents is reported as absent.
Where It Fits
Internal Knowledge Search
Find answers scattered across HR policies, work manuals, and approval history in one place. Repeat questions to the person in charge drop away.
- Unified search across policies, manuals, and records
- Department and role level access applied
- Source document and passage shown per answer
Contact Center Support
Surface product terms and policy clauses during a live call. New agents answer from the same evidence as experienced ones.
- Unified index of products, terms, and FAQs
- Similar case retrieval from past tickets
- Source wording available to copy verbatim
Technical Documentation Q&A
Find answers in design documents, API references, and incident history. Exact identifier search matters most where code and docs sit side by side.
- Exact search on code, config values, and identifiers
- Version-aware document separation
- Incident history linked to remediation records
Contract & Legal Review
Compare contract clauses against standard language and flag the differences. Reviewers get a narrowed set of points to check first.
- Clause-level deviation from standard language
- Similar contract retrieval
- Clause-level source tracing
What Makes It Different
Three Retrievals, Combined
Semantic vector search, exact-match keyword search, and structure and metadata search run together, then results are re-ranked. Employee IDs, clause numbers, and model names that vector search alone misses are caught.
No Evidence, No Answer
When no supporting passage is found, it says so rather than guessing. Unanswered questions are aggregated so you know which documents need filling in.
Sources Attached
The document and passage behind each answer are shown as-is. Users can open the original, and the trail holds up under audit.
Permissions Preserved
Existing document access rights apply to retrieval. Documents a user cannot open are excluded from results and from answer evidence.
Keeps Up With Changes
Connected to your document systems, additions, edits, and deletions are reflected automatically. Deleted documents never become the basis for an answer.
Quality in Numbers
Answer accuracy, evidence hit rate, and no-answer rate are measured and reported. See which question types are weak and improve documents and indexes accordingly.
How It Runs
01
Collect Documents
Gather target documents and normalize their formats
02
Build Indexes
Vector, keyword, and metadata indexes are built together
03
Tune Retrieval
Retrieval and answer quality are tuned with real questions
04
Operate & Measure
Usage data drives ongoing document and index improvement
Get in Touch
Pricing depends on document volume, systems to integrate, and security requirements. Available as cloud or on-premise. We run a proof of value on your own documents first.
Request a Consultation