On-Prem RAG Systems & Knowledge Bases
Retrieval-Augmented Generation that keeps your data on-premises and your answers accurate
Build secure, high-performance RAG systems that run entirely within your infrastructure. Connect proprietary knowledge bases to locally-hosted LLMs with hybrid search — keyword, semantic, and reranking — without exposing sensitive data to external APIs.
Book a Discovery CallThe Challenge
- Sensitive corporate data cannot leave your network, making cloud-based AI solutions a non-starter
- Enterprise knowledge is siloed across SharePoint, wikis, ticketing systems, and file shares with no unified search
- Generic LLMs produce hallucinations because they lack your organization's domain-specific context
- Existing search tools return keyword matches, not the contextual answers your teams actually need
Our Approach
Knowledge Audit & Data Mapping
Catalog existing knowledge sources across SharePoint, wikis, databases, and file shares. Assess data quality, access patterns, and map document types to embedding strategies.
RAG Pipeline Architecture
Design the end-to-end retrieval pipeline: embedding model selection, vector store configuration, hybrid search strategy (keyword + semantic + reranking), and LLM integration — all on-premises.
Embedding & Indexing Build
Build the document ingestion pipeline with intelligent chunking, generate embeddings, and index into the vector database with metadata for department and role-based filtering.
Search Tuning & Evaluation
Optimize retrieval accuracy with hybrid search scoring, implement evaluation frameworks against ground-truth Q&A pairs, and fine-tune reranking for your content types.
Deployment & Governance
Deploy to production with domain governance controls by department and role, monitoring dashboards, and operational documentation for your team.
What You Receive
Technology Integrations
Frequently Asked Questions
Ready to Transform Your Operations?
Start with a discovery call to discuss your challenges and explore how we can help.
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