Case Study · 2025
Sales Detect Agent
An autonomous multi-agent system that watches e-commerce deals, estimates competitive prices, and fires real-time alerts.
Context
E-commerce deals move faster than a human can re-read them. The system had to discover, compare, and alert — without spamming.
The Problem
Manual price watching is late and noisy. A single agent mixing discovery, analysis, and notification gets all three wrong.
Process
Split the jobs
Specialized agents for product discovery, price analysis, and notification orchestration — each with an LLM and a clear contract.
State and freshness
Intelligent scheduling and state management to track deal freshness and prevent alert fatigue.
Decisions
Many agents, one coordinator
One giant prompt hallucinates prices. Narrow agents correct each other.
Silence is a feature
Without freshness tracking, every deal re-fires. State stops the spam.
Outcome
✦ Autonomous real-time alerts on e-commerce deals
✦ Less noise — deal freshness is checked before notify
Reflection
“An agent is only useful if it knows when to stay quiet. Orchestration is as much filtering as action.”