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Micromaestro

Go · gRPC · ReactGITHUB ↗

Inspired by Kinaxis Maestro, built to explore how much of a supply chain decision engine you can build without the enterprise price tag or the vendor lock-in.
Rule-based engine evaluates inventory conditions (low stock threshold + supplier lead time exceeding the reorder window) and emits replenishment orders automatically. Rules are declared in a config layer, not scattered through business logic; changing a threshold doesn't require touching application code.
Go backend exposes a gRPC API with Protocol Buffers for type-safe, efficient communication between services. The React + TypeScript dashboard consumes it via grpc-web, receiving real-time inventory state without a REST polling loop.
Supports CSV and JSON inventory ingestion so the tool connects to existing data exports without a custom integration layer. Most supply chain data lives in spreadsheets, and that was a deliberate design constraint.
Scenario simulation module lets you run what-if analysis against current inventory state, testing rule configurations before applying them to live data. Useful for catching over-ordering or stockout conditions before they happen.
In-memory data store with the persistence layer behind an interface; a PostgreSQL migration path is planned and the swap requires no changes to business logic.

Tech Stack

REACT

TYPESCRIPT