FYLD raises $41M to scale AI for field operations and infrastructure
Updated: 10:00 EST / February 17, 2026
FYLD, a London-based AI startup focused on infrastructure and utility fieldwork, closed a $41 million Series B to speed up delivery of large-scale projects. The round was led by New York-based Energy Impact Partners with participation from Partech through its Growth Impact Fund. The company reported 82% year-over-year growth without breaking out specifics.
Founded in 2020, FYLD's platform blends AI risk assessment, digital work execution, and remote site visibility. Crews capture video, audio, photos, and text on mobile. An AI engine analyzes conditions in real time so managers can intervene earlier and crews can execute work right the first time.
"Infrastructure leaders know reactive management of their frontline workforce has never worked at scale," said co-founder and CEO Shelley Copsey. "By applying AI to real-time field data, they're replacing hindsight decisions with predictable, first-time-right delivery - and they're keeping fieldworkers safe."
Why operations leaders should care
FYLD reports up to a 48% reduction in serious workplace injuries among customers. Real-time, edge-based hazard detection supports storm response and low-signal environments. The result: faster issue resolution, fewer truck rolls, and tighter control of dispersed crews.
- Up to 48% reduction in serious injuries (since launch).
- Texas utility handled 67% of storm-related site hazards faster, cutting safety incidents.
- 36% reduction in management travel during storm events.
- Hazard prediction works even in low-connectivity storm zones.
Where it fits in your ops stack
Think of FYLD as the layer between the field and your control room. Crews document conditions on mobile; AI flags risks, sequences tasks, and supports remote approvals. Supervisors get visibility across multiple sites without hopping between spreadsheets, photos, and chat threads.
Sectors and scale
The platform targets asset-heavy operations: utilities, energy, civil engineering (highways and transport), construction, and heavy manufacturing. In 2025, FYLD expanded across the U.S., adding customers including Kiewit, Quanta Services, Emery Sapp & Sons, and Sulzer, alongside longstanding partner Ferrovial. The company expects more than 40% of total revenue to come from the U.S. by the end of 2026.
How to run a smart pilot
- Define hard KPIs: injury rate (TRIR), first-time-right percentage, rework rate, management travel time, and mean time to respond/repair.
- Start with high-risk, high-variance workflows (storm restoration, confined space, hot work, high-traffic roadworks).
- Test in low-signal areas to validate offline capture and edge detection.
- Set up clear escalation paths: who reviews AI flags, who signs off, and how fast.
- Integrate daily: video/photo standards, short-form risk notes, and supervisor feedback loops.
ROI framing for ops
Combine the cost of recordable incidents, lost time, rework, and supervisor travel. Add avoided outages or service penalties from faster hazard resolution. If AI-driven guidance lifts first-time-right while cutting incidents and miles driven, breakeven typically shows up within one or two high-impact workflows.
Investor signal
Backing from Energy Impact Partners and Partech's Growth Impact Fund points to sustained interest in AI that moves the needle on safety and execution, not just analytics. For operators, that means more scrutiny on measurable outcomes and deployment speed.
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