Enterprise Knowledge Intelligence Fabric
Knowledge curation for ChatGPT & Copilot agents
Agents are only as good as what they know. This is the layer that curates enterprise knowledge and serves it to ChatGPT and Microsoft Copilot agents — so they answer from trusted, current sources.
01Context
Enterprise knowledge lives in many places — knowledge articles, runbooks, product data, analytics. An agent pointed at all of it with plain search returns text that matches the question, not necessarily the answer.
And the people who need insight from that data are often not the people who can write the query.
The challenge: Turn scattered enterprise knowledge into a curated, connected capability that agents can ground their answers in — and that anyone can question in plain language.
02Approach
Build the Knowledge Management Service
Designed and developed an enterprise-wide Knowledge Management Service as the single place agents and people go for knowledge.
Add Generative BI
Natural-language, on-demand analytics, so questions about the data no longer wait on a dashboard or an analyst.
Connect structure and meaning
Semantic retrieval over knowledge graphs, vector search and GraphRAG, so answers carry relationships between systems, products and teams — not just matching text.
Serve it where people already work
Connected curated knowledge to ChatGPT and Microsoft Copilot agents for grounded answers and continuous knowledge curation.
03Architecture
04Key decisions
Graph plus vectors, not vectors alone
- Why
- Enterprise questions are often about how things relate — which product, which dependency, which team.
- Trade-off
- A knowledge graph is more work to build and maintain than an embedding index, but it is what lets answers reason across relationships.
Curation as a continuous process
- Why
- Knowledge goes stale, and stale knowledge makes confident, wrong agents.
- Trade-off
- Ongoing curation costs effort every week; the payoff is answers people can trust.
Natural language as the interface to analytics
- Why
- The people with the questions are rarely the people who write SQL.
- Trade-off
- Generative BI needs guardrails on what it can query, in exchange for self-serve insight.
05Outcomes
- One enterprise knowledge service for agents and people.
- On-demand analytics in natural language through Generative BI.
- ChatGPT and Copilot agents grounded in curated enterprise knowledge.