The problem
Most firms don’t actually look at their own historical data. The data is there, reports get generated, but every time someone has to decide — “what should we do for this client”, “what’s moving in this sector”, “what did we miss last month” — they answer it from scratch, by hand. Result: slow reaction, intuition-led calls, lost hours.
Approach
For two firms we built a per-client AI agent layer that takes over those routine tasks. Every agent is bespoke — not a generic assistant trained on someone else’s data.
- Data interpretation agent — sweeps the firm’s historical sales, operations, and client data on a schedule, surfaces meaningful patterns.
- Market research agent — scans sector movements, price trends, and competitor signals; produces interpretation tailored to the client, not just raw news.
- Demand drafting agent — prepares client-specific quote and demand drafts based on each customer’s profile; the human only approves.
- Statistics panel — the operation’s pulse in a single visual: interpreted numbers, not raw tables.
Outcome
In active use at both firms. The opening question of every week — “what should we be looking at this week?” — is now answered by opening the panel rather than doing manual research.
Important note: agent logic, prompt libraries, and data models stay with the client as their competitive edge. This page describes the methodology; the proprietary business rules are not shared.