What is Repair AI?
Repair.ai keeps factories moving. It finds and fixes problems faster, learns from every operation, and builds an industrial memory that connects machines and teams. The result fewer failures, faster interventions, and factories that stay productive, profitable, and aware of themselves.
Problem
Users in industrial settings currently rely on manual troubleshooting and reactive maintenance. Delays in identifying and resolving equipment issues lead to unplanned downtime, reduced productivity, and higher costs.
Solution
An AI-powered industrial optimization platform where users can automatically detect, diagnose, and resolve machinery issues in real time, while building a self-learning "industrial memory" to prevent future failures. Examples: predictive maintenance alerts, root-cause analysis, knowledge-sharing dashboards.
Customers
Maintenance managers, plant engineers, and operations directors in manufacturing, energy, or heavy industries (demographics: 30–50 years old, tech-savvy, focused on efficiency metrics).
Unique Features
Self-learning industrial memory that connects machine data with human insights, adaptive problem-solving without predefined rules, and real-time collaboration tools for cross-team interventions.
User Comments
Cut troubleshooting time by 40%
Reduced unplanned downtime by 25%
Intuitive interface for non-technical staff
Seamless integration with legacy systems
Proactive alerts prevented costly breakdowns
Traction
Launched 6 months ago; used by 120+ factories globally, $35k MRR, featured in 3 industrial tech newsletters, founder has 2.2k LinkedIn followers.
Market Size
The global predictive maintenance market is valued at $6.2 billion in 2023, projected to grow at 25.2% CAGR through 2030 (Grand View Research).
