Novara Robotics
Novara Robotics offers Deri, an AI reliability engineer for factories that connects live equipment data with manuals, work orders, and past incidents to detect issues early and speed up recovery. The platform prioritizes incidents, ranks likely causes, and guides technicians through repair procedures, tracking metrics like early-warning lead time and MTTR. It deploys on cloud or on-premises and integrates with existing machines, sensors, MES, and CMMS systems.
- Manufacturing / Industry 4.0
- Artificial Intelligence
- AI Agents
- Industrial Automation
- Internet of Things
- Software Only
- Data & Analytics
Funding
Founders
Founder details are not available yet.
Product
Problem
Factory equipment failures cause unplanned downtime, and technicians often rely on scattered information sources to diagnose problems. The disconnect between live machine signals, historical incidents, and maintenance documentation slows response times and extends production losses.
Solution
Deri acts as an AI reliability engineer that connects live equipment data with manuals, work orders, and past incidents to help teams detect issues earlier and recover faster. The platform detects emerging issues and shifting equipment behavior, prioritizes them, and routes them to the right person. It pulls together live signals, operational context, and historical incidents to rank likely causes, then shows technicians the procedures needed to restore production. After resolution, Deri documents the fix and adds it to the equipment's history for future reference, establishing measurable baselines for early-warning lead time, time to diagnosis, mean time to repair, and unplanned downtime.
Target Audience
Primary customers are manufacturing facilities and factory operations teams that rely on complex equipment, including plants using robots, sensors, MES, and CMMS systems, who need to reduce unplanned downtime and improve maintenance efficiency.
Features
- Equipment behavior monitoring that detects emerging issues before failures occur
- Incident prioritization and automatic routing to the appropriate technician
- Root-cause analysis combining live signals, operational context, and past incident history
- Step-by-step recovery guidance pulled from manuals and documented procedures
- Continuous learning loop that records fixes into equipment history for faster future responses
- Performance tracking for early-warning lead time, time to diagnosis, MTTR, and unplanned downtime
- Flexible deployment options including cloud and on-premises
- Integrations with machines, robots, sensors, MES, CMMS, and existing technician workflows