RAG-Powered Knowledge Assistants
Chat with your data — grounded, cited, trusted
We build retrieval-augmented generation systems that turn your fragmented documents, wikis, and records into a single queryable source of truth. Whether it's customer support deflection, internal knowledge lookup, or research acceleration — every response is grounded in your actual data, not hallucinated from training.
- Category
- Data & Insights
- Status
- Active
- Tier
- core
- Delivery
- In-house
- Steps
- 4-phase engagement
What we deliver.
Every capability is engineered for production from day one — tested, documented, and ready to deploy.
- Custom knowledge base ingestion from docs, PDFs, wikis, and databases
- Hybrid search with semantic + keyword retrieval
- Citation-backed answers with source document linking
- Incremental content updates without full re-indexing
- Role-based access control on knowledge sources
- Multi-format output — chat widget, API, Slack/Teams integration
How the engagement runs.
Data Mapping
Audit your content sources, formats, and access patterns to design the ingestion pipeline.
Retrieval Design
Build the chunking, embedding, and search strategy tailored to your content types.
Integration Build
Connect the assistant to your tools — website widget, Slack, Teams, or custom UI.
Tuning & Handoff
Evaluate accuracy against real queries, tune retrieval, and hand off with documentation.
Deployed RAG assistant (chat UI or API)
Content ingestion pipeline
Admin dashboard for content management
Integration with your existing tools
Ready to put this into action?
Tell us about your project and constraints. We'll respond with a technical point of view.
Get in touchLet non-technical staff query data in plain English