
Material Intelligence & Data Automation System — cleans, classifies and governs the material master, and stops new duplicates at the door.
Every industrial operation keeps a material master: the list of every motor, bearing, valve, spare part, raw material and consumable it buys, stores and tracks in its ERP. Built up over decades by different people in different ways, it fills with duplicates, vague descriptions, missing manufacturers and specifications, and inconsistent units and classifications.
MIDAS reads those messy, real-world descriptions and turns them into clean, structured, standards-aligned records. Each record passes through a layered pipeline — the cheapest and most reliable methods first — and every result carries a confidence score and a source attribution: which layer made the call, and why. Nothing is a silent guess.
On top of that intelligence sits the full material lifecycle: search-first creation that checks for an existing part before a new one can be made, structured technical and commercial review, controlled changes and extensions, and integration-ready export. MIDAS runs on your own infrastructure with local language models by default; external AI services are an explicit, opt-in choice, never a requirement.
- The same part entered many times under different descriptions
- Missing manufacturers, specifications and classification codes
- No quick way to answer “do we already have this part?”
- Audits that expect clean, traceable material data
What you get
- Automatic classification using engineering knowledge, not keyword matching
- Structured attributes extracted from free-text descriptions
- Duplicate, near-duplicate and interchangeable part detection
- Standardised short and long descriptions, mapped to classification standards
- Search-first material creation and a multi-stage approval workflow with a full audit trail
- Bill-of-materials and equivalent-parts intelligence
- On-premise by default — auditable by design


