Elyos AI raises $13M to scale AI front-office agents for trades and field services
Image Credit: Elyos AI
Elyos AI, a UK startup building AI agents for the trades and field services industry, has closed a $13 million Series A led by Blackbird Ventures, with participation from Y Combinator and Pi Labs. The new round brings total funding to $16 million and will fuel product development and international growth.
Founded in 2023 as part of the Y Combinator program, Elyos AI focuses on one job: acting like reliable front-office staff for busy trades teams. The agents answer inbound calls, follow up on missed calls, handle outbound communication, manage email workflows, and book jobs directly into the systems trades businesses already use.
What the product actually does
These agents aren't generic chatbots. They take calls, respond over voice, email, and messaging, and integrate with job management software to schedule work without creating new admin or duplicate records.
As co-founder Adrian Johnston puts it: "Trades businesses are overwhelmed by calls, emails, and admin, and that friction directly costs them revenue. We're building AI agents that work like effective front-office staff: answering every call, booking every job, and integrating deeply into the systems trades already use."
The company targets plumbers, electricians, HVAC teams, fire and security operators, and facilities managers. Always available, integrated into existing workflows, and trained for the realities of the trade, the agents focus on speed to answer, accurate booking, and clear follow-through.
Early results from the field
Customers report higher booking rates, faster responses, fewer missed calls, and lower overhead. Amax, a fire and security company in London, shared a concrete outcome: "Elyos AI agents now handle 30% of technical calls with no human intervention. We're now in a situation where we can't imagine not working with Elyos."
Why teams are paying attention
The founding team has deep field operations experience. Philippa Brown and Panos Stravopodis worked at OVO and Bulb Energy, where Brown ran operations for over 1,000 engineers and Stravopodis built the operating systems those engineers used daily. Johnston is a second-time founder; his previous company, Una Brands, reached $70 million ARR and raised $100 million.
Investors point to two things: a massive vertical with clear workflow pain, and voice agents that perform in live environments. Blackbird's James Palmer noted the market depth and how well Elyos's agents perform with real customers. Pi Labs' Faisal Butt emphasized that trade services have been underserved by modern software and that Elyos helps teams capture more revenue and improve customer experience with leaner ops.
Roadmap and hiring
With this round, Elyos will expand engineering, operations, and go-to-market teams. The company plans deeper integrations with leading field-service job management systems and new agent capabilities across voice, email, and messaging. International expansion is planned for 2026, and hiring is open across engineering, product, operations, and GTM.
What this means for support and product leaders
- Voice is viable for complex, real-world workflows when it's integrated into the job stack and measured on completion, not deflection.
- "Answer every call, book every job" is a crisp north star. It aligns support KPIs (pickup rate, first-contact resolution) with revenue outcomes (completed bookings, fewer no-shows).
- Agent performance depends on software integration depth. Expect the best results when the agent reads/writes directly to your job system with audit trails.
- Human-in-the-loop stays important. Route edge cases, urgent issues, or compliance-sensitive scenarios to people with clear handoffs.
How to evaluate an AI agent for field services
- Coverage and accuracy: What percentage of inbound calls and emails can the agent fully resolve? How does it perform by intent (quote requests, emergencies, reschedules)?
- Latency: Time to answer and time to first action. Long delays erase trust.
- Systems integration: Can it check availability, create bookings, update customer records, and log outcomes without manual cleanup?
- Tone, policy, and compliance: Does it respect operating hours, pricing rules, and escalation policies? Can you customize tone by brand or job type?
- Monitoring and QA: Are transcripts, sentiment, and outcomes reviewable? Is continuous improvement built in?
- Handoff quality: Is there a clean path to a human with full context, especially for urgent or safety-related issues?
- ROI model: Track booked jobs, saved headcount hours, reduced missed calls, and NPS. Verify results in a limited rollout before scaling.
Market context
This raise lands as UK tech-especially AI-continues to attract strong investor interest, supported by steady late-stage and growth capital. For broader context on European tech funding trends, see the State of European Tech reports by Atomico here.
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