RAG / Knowledge Base Agent
Answers grounded in your actual documents.
Builds retrieval-augmented generation pipelines over your docs, wikis, tickets, and code. Chunks, embeds, retrieves, re-ranks, and generates with source-citation. Zero hallucination tolerance - if the retrieval confidence drops, it escalates to a human.
Trusted by teams backed by
What this agent actually does.
Every capability below is production-ready. When we stand this agent up for your team, we configure each capability to your data, your voice, and your guardrails - you see draft outputs before anything goes live. No speculative roadmap items; no "coming soon."
Document ingestion + chunking strategy per content type
Embedding + vector DB selection (pgvector / Pinecone / Turbopuffer)
Hybrid retrieval (semantic + BM25) + re-ranking
Citation-aware generation
Confidence thresholding + human handoff
Wired into the stack you already run.
The agent reads from and writes to these systems via official APIs. Auth is scoped per action, rate-limited, and audit-logged. If your stack uses a tool not listed here, we add it - the integration surface is extensible.
pgvector
Pinecone
Turbopuffer
Weaviate
Notion
Confluence
Intercom
Questions from Professionals Like You
- Standard deployment is 24–48 hours from green-lit scope. A custom configuration on top of this agent (unique data sources, bespoke workflows, compliance reviews) typically lands in 2–3 weeks. We never estimate agent delivery in months for a single-agent engagement.
- No. The RAG / Knowledge Base Agent augments your team - it handles the high-volume, repeatable work so humans can spend their time on judgement calls and relationships. Every agent output is reviewable; every action is logged; every escalation routes to a named owner on your side.
- Yes. The agent does not replace your ai enablement platform - it operates it. Integrations are via official APIs, so nothing about your existing workflows, permissions, or audit trails changes.
- We build guardrails and confidence thresholds into every agent. Below the threshold, the agent escalates to a human rather than guessing. Weekly conversation review catches drift; monthly evals measure accuracy against a frozen golden-path test suite. When something needs correction, the fix ships within 48 hours.
Ready to stand up your RAG / Knowledge Base Agent?
Book a scoping call and we'll walk you through exactly how the RAG / Knowledge Base Agent integrates with your stack, what the first 30 days look like, and how we measure whether it's actually working.