Cambridge-based condition monitoring specialist beats global field to win one of industrial technology’s most competitive startup programmes.
We are proud to announce that Faraday Predictive has been named the winner of the Motion High Power division at the 2026 ABB Startup Challenge, one of the most competitive and prestigious startup programmes in the global industrial technology sector.
This is a significant milestone for our team, and we want to share the full story of how we got here, what we built during the challenge, and what this recognition means for the future of scalable predictive maintenance.
What is the ABB Startup Challenge?
Now in its seventh year, the ABB Startup Challenge is ABB’s flagship global innovation programme. It brings together startups from around the world to co-develop solutions that address some of the most pressing challenges facing industry, energy, and infrastructure today.
The programme operates through a proven, non-equity partnership model. Selected startups work directly with ABB’s engineering and business teams to develop a Minimum Viable Product (MVP), with access to ABB’s shared lab environments, technical expertise, and customer networks. Since its launch in 2020, the programme has invested $23 million in startups, supported the development of 35 MVPs, and helped launch eight solutions to market.
The 2026 edition focused specifically on AI-powered technologies to improve energy efficiency, resilience, and sustainability across industries and power grids. The Motion High Power challenge sought solutions to optimise electrical motor and drive systems, where incorrect parameterisation, limited diagnostics, and poor visibility into machine condition continue to drive significant energy waste and unplanned downtime across the industry.
You can read more about the ABB Startup Challenge at: abb.com/startup-challenge-2026
How Faraday Predictive Got Here
Following a competitive application phase, Faraday Predictive was shortlisted to take part in an intensive 10-day challenge. The brief was clear: develop and demonstrate a credible MVP concept in collaboration with ABB’s teams, showing both technical feasibility and a viable path to deployment at scale.
From the outset, our approach centred on a problem we have been working to solve since the founding of the company: the barriers that prevent predictive maintenance from being adopted at scale. Traditional condition monitoring deployments require additional sensors, complex cabling, specialist installation, and ongoing hardware maintenance. For most industrial operators, that combination of cost and complexity puts genuine predictive capability out of reach.
Our answer was to remove the hardware entirely.
Rather than adding new sensors to the system, our approach enables Faraday Predictive’s algorithms to run directly on ABB drives, using the voltage and current data already flowing through the drive. The motor itself becomes the sensor. No additional hardware. No cabling. No complex installation process. Just advanced condition monitoring embedded into the infrastructure that is already there.
During the 10-day challenge, we successfully demonstrated the ability to ingest and process ABB drive data through the Faraday platform, validated the technical feasibility of the approach, and set out a clear MVP roadmap. At the end of that phase, we were selected as one of three finalists in the Motion High Power category.
The Grand Finale in Bilbao
The final stage of the challenge brought together the shortlisted teams to Bilbao on the 15th and 16th of April 2026, running alongside one of Europe’s largest climate technology conferences.
Over two days, we had the opportunity to present the MVP framework in depth to ABB’s final judging panel, work through the technical and commercial dimensions of the proposed partnership, and share our broader vision for how scalable, non-invasive predictive maintenance can transform how rotating equipment is monitored across industry.
The format was genuinely collaborative. Beyond the formal presentations, we had direct access to ABB’s engineering and business teams, the chance to discuss real-world deployment scenarios, and the opportunity to sharpen the roadmap based on expert feedback from people who understand the industrial motor and drive market better than almost anyone.
At the conclusion of the event, Faraday Predictive was announced as the winner of the Motion High Power division.
What We Built and Why It Matters
The solution we demonstrated during the ABB Startup Challenge builds directly on the core technology that Faraday Predictive has been developing and refining for years: sensorless, physics-based condition monitoring using only the voltage and current signals that motors and drives already produce.
By embedding our patented algorithms directly into ABB drives, we can turn any ABB-driven motor system into a condition monitoring device, without adding a single sensor to the installation. The system detects:
- Mechanical faults, including bearing wear, rotor asymmetry, and misalignment
- Electrical anomalies, including supply imbalance, harmonic distortion, and winding issues
- Operational problems, including cavitation, throttling, and process load variation
- Energy waste, enabling operators to identify inefficiencies before they become failures
The result is early failure warnings, the ability to schedule maintenance proactively, and a significant reduction in unplanned downtime, all delivered through infrastructure that is already installed and running.
What makes this approach genuinely scalable is the absence of the usual barriers. There is no hardware procurement, no installation project, no sensor calibration, and no ongoing hardware maintenance. The solution integrates into ABB’s existing drive ecosystem at no added complexity or cost, which means it can be deployed across an entire fleet of motor-driven assets far more quickly and economically than any sensor-based alternative.
To understand more about the technology behind this approach, see our overview of MBVI systems: faradaypredictive.com/mbvi-technology/
What Comes Next
Winning the ABB Startup Challenge is not the end of the process. It is the starting point for a structured collaboration.
The immediate focus will be moving from demonstrated feasibility to a validated, deployable solution. That means working closely with ABB’s teams to refine the integration, identify pilot customer sites, and build the evidence base that will support broader commercialisation.
We are under no illusion about the work still ahead. But the direction is clear, and the partnership with ABB gives us access to an industrial installed base, technical depth, and commercial reach that would be very difficult to build any other way.
A Word of Thanks
This result reflects the effort of the entire Faraday Predictive team, and we would like to take a moment to acknowledge the people who made it possible.
Thank you to ABB, the judging panel, and everyone involved in organising and running the Startup Challenge. The quality of the process, the depth of the technical engagement, and the genuine spirit of collaboration throughout were exceptional.
Thank you also to our own team, whose commitment to the vision of accessible, scalable predictive maintenance has never wavered, and to our customers and partners whose trust and feedback continue to shape everything we build.
The Bigger Picture
We have believed from the beginning that predictive maintenance has a fundamental scalability problem. The technology to detect faults early and prevent unplanned failures has existed for decades. What has held back widespread adoption is not the capability but the deployment model: too much hardware, too much complexity, too much cost per asset.
The approach we demonstrated during the ABB Startup Challenge is our answer to that problem. By working within existing infrastructure rather than adding to it, we can bring genuine condition monitoring to far more assets, at far lower cost, than has been possible before.
The combination of ABB’s industrial expertise, global installed base, and customer relationships with Faraday Predictive’s analytics creates something that neither organisation could build alone. We believe the potential to transform how rotating equipment is monitored across the industry is real, and this partnership is a significant step towards making that happen.
We look forward to sharing more as the collaboration develops.