Build a private RAG system your team can trust.
SheltSoft designs retrieval-augmented generation systems for organizations that need accurate answers over internal documents, policies, product knowledge, and operational content.
Free 30-minute scoping call. No commitment.
- Private deployment on your cloud or infrastructure
- Grounded answers with source-aware retrieval
- LLM flexibility: hosted APIs or local models
- Integration with document stores, portals, and internal tools
A practical RAG approach for business teams
We focus on the parts that matter in production: reliable retrieval, private deployment when needed, and a clean path from documents to trustworthy answers.
Grounded, source-aware answers
RAG reduces hallucination risk by retrieving relevant context before generation. That makes it a strong fit for policy, product, support, legal, and operational knowledge.
Your data stays in your environment
When privacy and control matter, we can deploy on your infrastructure and adapt the setup to your access, compliance, and hosting requirements.
Designed for production retrieval
A good RAG system depends on chunking strategy, metadata, access control, indexing jobs, evaluation, and monitoring, not just a vector database.
How a SheltSoft RAG system works
- 1Step 1:Ingest documents, knowledge bases, and system data
- 2Step 2:Clean, segment, enrich, and index content for retrieval
- 3Step 3:Retrieve the best matching context at question time
- 4Step 4:Generate answers with references and workflow controls
Typical RAG use cases
RAG is strongest where answers need to stay close to your approved information and where people lose time searching, comparing, or confirming details manually.
- Internal knowledge assistants for HR, operations, and IT
- Support copilots grounded in manuals, policies, and product updates
- Document search across contracts, procedures, or technical documentation
- Secure client-facing knowledge assistants with curated sources
Frequently asked questions
Where does our data live?
Wherever you need it to. We can deploy fully on your own cloud or on-premise infrastructure, so your documents and indexes never have to leave your environment.
Can we use our own LLM or keep everything local?
Yes. We're not tied to one provider — we can wire up hosted APIs, your existing enterprise contracts, or fully local, open-weight models depending on your privacy and cost requirements.
Do we need to change our current systems?
No. We build the retrieval layer around your existing document stores, wikis, and portals instead of asking you to migrate content into a new platform.
How long does a RAG project usually take?
Most first deployments launch in 4-8 weeks, starting with one well-defined knowledge domain so you can validate answer quality before expanding scope.
Need reliable answers over private knowledge?
We can help you choose the right retrieval strategy, build the indexing pipeline, and deploy a RAG experience that fits your systems and governance model.
Free 30-minute scoping call. No commitment.