Case study
Client identity, people, source lists, outputs, and commercial terms withheld.
Interactive demo
Walk this install chapter by chapter: discovery, setup, the team views, one decision traced from request through delivery, and the outcomes.
Pipeline influenced (business development conversations sourced from platform briefings)
Executives and companies monitored (across the firm's approved sources, growing monthly)
Signals in a single brief (news, thought leadership, competitor publications, executive moves)
Production AI agents (handed over with full documentation)
Team expansion (through internal referrals, not sales)
First system live (from kickoff to a working intelligence system)
Senior leaders at this scale live on signal: an executive changes roles, a competitor publishes, a market moves, and the first firm in the room wins the work. The research existed, but it arrived as documents on request, days late, rebuilt from scratch for every leader who asked. Each new request spawned another standalone tool with its own rules, and none of them made the next one cheaper.
We traced how intelligence moved from a leader's question to a delivered answer. The same failures kept appearing:
The firm did not need another research document. It needed an intelligence platform that turns recurring leadership questions into agents that answer them every day.
One platform now owns the full path from signal to briefing: intake, monitoring, agents, delivery, and cost control.
Watches thousands of companies, executives, publications, and market events across the firm's approved sources. One detected change can feed every team that cares about it, without being collected twice.
Nine documented agents run the recurring intelligence work: executive moves, competitive activity, market shifts, and sector briefings. Findings are combined, deduplicated, and delivered as finished briefs.
New intelligence needs enter one door with an audience, a question, sources, cadence, and an owner. Overlapping requests become platform additions instead of another standalone tool.
The same monitored signal renders differently for different desks. A new senior user gets a tailored view without cloning another executive's profile.
Every agent reports the cost of every run. Leadership compares agents like business units and scales the ones that earn it.
Anonymized installation
The engagement record covers the six-day first build, the expansion from one team to four-plus, the consolidation of overlapping tool requests, and the handover of nine documented production agents.
The firm, its people, teams, sources, outputs, and commercial terms remain private.
How one six-day build became the firm's intelligence layer.
The firm received nine documented production agents and the platform they run on: one intake for new intelligence needs, shared behavior kept separate from personal preferences, and per-run cost visibility. New requests extend the platform instead of starting over.
The strongest signal was not a metric. It was senior leaders across the firm asking for the platform by name and pushing their own teams onto it. Internal demand is the one adoption curve you cannot fake.
For the build decisions, controls, and operating model behind this installation, read Nine Agents Inside a Consulting Firm: A Build Teardown.
Client identity, people, source lists, outputs, and commercial terms withheld.
