Trapped inventory surfaced across the network in the first quarter.
Pharmacy Network Intelligence
Before
Days of cross referencing
Now
Minutes per question
The challenge
A multi site pharmacy network held drug, store, sales, inventory and out of stock data in separate systems. Every leadership question became a manual cross referencing exercise, so stockouts and dead stock persisted side by side.
What we built
An agent based layer sits on top of the existing databases. A multi agent architecture routes each plain language question to the right database, joins across five tables and returns an answer with a recommendation attached. No technical skill required.
How it runs
- ConnectFive databases joined into one queryable layer
- RouteAgents send each question to the right source
- RecommendAnswers arrive with an action attached
The result
- Excess
- Trapped inventory surfaced network wide
- Fewer
- Stockouts through optimised order levels
- Minutes
- To answer a cross database question
Built with
- MCP agents
- Natural language query
- Multi database
Run this in Pharma & Life Sciences
The same Decision support build, scoped to your sources and your reporting lines.