The retrieval layer every AI use case depends on.
Governed, evaluated retrieval across product, policy and playbook content — one knowledge layer powering self-service, agent assist and enterprise copilots.
Every AI team builds its own RAG. None of them govern it well.
Retrieval quality is the ceiling on AI quality. Without a governed knowledge layer, every use case rebuilds ingest, chunking, evaluation and access control from scratch — badly.
- Stale contentAnswers grounded in yesterday's policy destroy trust.
- No access controlOne employee sees another region's confidential playbook — a compliance incident waiting to happen.
- No evaluationRetrieval quality regresses silently. Nobody notices until customers complain.
A managed knowledge layer, not a library of scripts.
Connectors for SharePoint, Confluence, ServiceNow, Salesforce Knowledge, product docs, wikis and file shares.
Content-aware chunking with model-appropriate embeddings and per-domain tuning.
Per-role, per-region and per-persona retrieval boundaries, honored by the LLM.
Golden sets per use case, offline and online evals, and drift monitoring on every content update.
Every answer carries source citations that agents and customers can verify.
Managed content lifecycle: ingest, review, publish, evaluate and retire.
A six-step model, from assessment to managed operations.
Every engagement follows the same rhythm — so business, IT and delivery stay aligned from opportunity to outcome.
Content inventory and use-case fit.
Knowledge model, access control, evals.
One use case, calibrated retrieval.
Pipelines, access control, observability.
Additional use cases on the same layer.
Managed knowledge operations.
Use cases already in production with enterprise clients.
Grounded answers on web, mobile and voice with citations customers can follow.
Real-time knowledge for contact-center agents inside the CCaaS desktop.
Sales, HR, IT and operations copilots grounded in role-appropriate enterprise content.
Answers with defensible sourcing for regulated processes and audits.
Grounded on your data. Governed on day one.
Every platform we implement is only as good as the retrieval, connectors and controls behind it. These are the horizontal solutions we ship with every engagement.
Questions buyers ask us first.
- Do you require a specific vector database?
- No — we work with the vector store or hybrid search stack you already run, or recommend one for greenfield deployments.
- How is access control enforced?
- At retrieval time. Documents are filtered against the requester's identity and role before they reach the LLM.
- Can this power more than customer service?
- Yes — one knowledge layer powers self-service, agent assist, employee copilots and enterprise search.
Book a working session with our knowledge ai & rag for contact centers team.
30 minutes. Your architecture, your data, your KPIs. You leave with a concrete pilot outline and a business case worth defending.