StirLight
Develops StirSense, a proprietary machine learning platform for real-time in-process anomaly detection and traceable quality records for friction stir welding (FSW), enabling digital verification and scaling of this advanced joining process.
- CEO / Founder
- Toby Savage-Yu
- Team Size
- 1-10
- Stage
- Pre-Seed
- Total Funding
- $1.6M
- Latest Round
- Pre-Seed
- Key Investors
- Haatch Ventures; British Business Bank; D2N2; Innovate UK; Aerospace Technology Institute (ATI)
Technology & Products
Key Products
StirSense Process Monitoring Platform; Friction Stir Welding (FSW) Services
Technological Advantage
Proprietary StirSense platform fuses multi-sensor data streams with machine learning to detect defects in real-time, providing a digital thread for traceability. This data advantage creates switching costs and is protected as a trade secret, though the core ML approach is replicable by well-funded competitors.
Differentiation
Value Proposition
Eliminates the bottleneck of expensive post-weld inspections for FSW by providing real-time quality assurance, reducing inspection costs by up to 90% and enabling high-volume production of certified components.
How They Differentiate
Focuses on in-process quality assurance software for FSW, unlike hardware-focused welding equipment manufacturers. Provides a digital verification layer that integrates with existing FSW systems to enable certification and scaling.
Market & Competition
Target Customers
Manufacturers in aerospace, automotive, defense, and nuclear sectors requiring high-strength, lightweight, and safety-critical welded joints.
Industry Verticals
Aerospace; Automotive; Defense; Nuclear
Growth & Milestones
Growth Metrics
Secured £1.25 million in April 2026 to accelerate commercialization; company has been trading since March 2024 and generating revenue from FSW services.
Major Milestones
Secured £1.25M funding package (April 2026); Commercial launch and revenue generation from FSW services (March 2024); Development of StirSense proprietary platform