RAG & KNOWLEDGE GROUNDING
AI That Answers From Your Data. Not From a Guess.
RAG built for messy enterprise reality. Agents stay grounded in live, authoritative information with every answer cited and traceable. Built with the FDE framework.
Schedule a ConsultationUngrounded AI Is a Liability, Not an Asset
An AI answering from training data alone is operating on a frozen snapshot. In regulated industries that's a risk. Policy documents get updated. Medical necessity criteria change. Most RAG implementations don't survive contact with real enterprise document stores.
HOW WE DO IT
Grounded in Your Live Data. Built for Enterprise Complexity.
Intelligent Chunking & Indexing
Document-aware splitting that preserves context across tables, headers, and nested structures.
Hybrid Retrieval
Semantic + keyword search combined. Neither alone handles enterprise vocabulary, acronyms, and domain terms.
Source Citation in Every Response
Every claim traced to document, page, and paragraph. Auditable by compliance teams without engineering support.
Live Data Connectivity
Connected to live document stores, not batch-uploaded snapshots. When your source of truth updates, so does the AI.
Conflict Resolution
Overlapping documents handled with version awareness, recency signals, and authority hierarchies.
Metadata-Aware Retrieval
Filters on department, date, document type, and access level before semantic matching begins.
Evaluation & Scoring Before Deployment
Retrieval quality measured and scored against ground truth before any system goes live. No guessing at production accuracy.
WHERE IT PAYS OFF
Industries That Need Every Answer Cited
Insurance
Policy Q&A, coverage interpretation, benefits explanation grounded in live policy documents.
Healthcare
Medical necessity determination, clinical protocol lookup, formulary guidance with traceable citations.
Regulatory
Regulatory grounding, audit-ready citations, compliance checks against current-version regulations.
Enterprise Knowledge
Ops manuals, HR policy, technical documentation — searchable and answerable with source attribution.
IN PRODUCTION
In Production: Sectona
Sectona needed to generate complex technical proposals from RFPs stored on private SharePoint. The system retrieves relevant content, assembles structured responses, and cites source documents throughout.
10 days → 2 days
Proposal preparation time
80–90%
RFP coverage addressed automatically — client-verified
Deployed on private secured Azure AI Foundry. No data leaves the client environment.
Your Knowledge Base Deserves Better Than Keyword Search
Show us your document corpus. We'll tell you what production-grade RAG looks like for your environment — in six weeks.
Schedule a Consultation