01
The difficult problem
Maintenance, procurement and operating data were separated across enterprise systems and fleet locations.
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Industrial operations intelligence
RigMind AI
An operations-intelligence layer unifying fleet health, failure risk, maintenance and inventory across drilling assets.
AutonomousPlatformResearchInfrastructure
The brief
Built around the hard part.
02
The intelligence built
A unified asset model supports health scoring, remaining-useful-life forecasts, root-cause analysis and grounded answers.
System architecture
How the system works.
The model is one layer. The value comes from connecting inputs, intelligence and production action as one accountable system.
- 01
Fleet data model
Acquire and structure the operating signal.
- 02
Risk and survival engine
Transform it through the model, rules and control layer.
- 03
Intelligence layer
Deliver a decision, artifact or action into production.
In production
Where it runs.
Deployment
Command-center experience designed to sit across established industrial systems.
What it changes
Operators move from fragmented records to one ranked view of fleet risk.
Production stack
- Next.js
- TypeScript
- Survival models
- LLM copilot
- Static export