A foresight consultancy produced high-value futures research — and that value stayed locked in reports only the team knew how to navigate. We turned the knowledge base into an AI agent that answers open and closed questions with context, anchored in the consultancy's real archive. Clients began exploring possible futures interactively and on their own.
| Indicator | Before | After | Δ |
|---|---|---|---|
| Team time answering questions | High | — | — |
| Client autonomy over the knowledge base | None | Full | — |
Knowledge base ──┐
(research · reports) ├──► Indexing (RAG) ──► AI agent ──► Chat (web · mobile)
└─► Open and closed questions · strategic insightsThe consultancy produced high-value futures research — and that value stayed locked in reports only the team knew how to navigate. Every client question became a queue on the team. The knowledge existed; what was missing was a way to reach it without a middleman.
The point wasn't to put a generic chatbot in front of the archive. It was to anchor the agent in the consultancy's real content — so it answers open and closed questions with context, not with a loose model's guess. We structured the base, indexed the archive and built the agent on top, integrated with the content clients already pay to receive.
Clients began exploring possible futures interactively and on their own, generating their own strategic insights from the base. The team gained scale and cut support time — and rather than pushing clients away from the content, the agent deepened their use of it. AI inside the firm's knowledge operation, not a parallel demo.
Same Diagnosis structure: 3–5 weeks, locked scope, measurable KPI. Talk directly to a partner.