Ekansh Mittal, the Head of Digital Innovation and Commercial Strategy, credited with driving Spotta’s global expansion and multi-million pound growth in the agritech sector, has officially stepped down from his leadership role. He has now joined Energy Research Lab (ERL), a UK-based deeptech venture focused on energy-saving AI and sensor technologies, to spearhead product development and commercialisation across the UK and European indoor farming markets.

Mittal’s move marks the next phase in a career that has consistently bridged deep science and scalable product innovation. During his four-year stint at Spotta, he led the company’s transformation from a Cambridge research spinout to a commercial-scale solution deployed across Brazil, the Middle East, and Europe. Under his leadership, Spotta’s agritech platform helped growers improve yields while significantly reducing their dependence on environmentally harmful pesticides.

As a result of Mittal’s efforts, the UK-based agritech scale-up recently raised $4M in funding from strategic VC investors and Innovate UK, aimed at expanding the technology into new global markets.

At Energy Research Lab, Mittal will focus on translating lab-tested technologies into market-ready products. His new mandate includes forming global partnerships in energy-efficient indoor agriculture and large-scale climate analytics. ERL, backed by patient private equity investors, is building intelligent infrastructure for carbon-conscious crop management and sustainable food production.

“Spotta was a deep and fulfilling ride—transforming scientific insight into meaningful agricultural outcomes,” Mittal said.
 “At ERL, I see a chance to apply those same principles to even more complex environments like climate-sensitive farming. The mission remains the same: build tech that matters, and scale it responsibly.”

Prior to Spotta, Mittal held senior roles at Kent and co-founded a high-growth edtech venture in India. His career has spanned deeptech commercialisation across sectors including IoT, cleantech, and AI-enabled public infrastructure.

Spotta is expected to continue scaling its pest intelligence platform globally. Mittal will remain involved in an advisory capacity through mid-2024, ensuring a smooth transition of strategic partnerships and market development efforts.

Startup77 will continue to track Mittal’s journey and ERL’s evolving product roadmap as deeptech reshapes the global economy.

By Ekansh Mittal

There’s a saying in forestry: if you want to understand the forest, you can’t just study the trees. You need to see the whole system – soil, weather, wildlife, and time.

That mindset holds true for deploying AI in complex, real-world environments.

In 2022–23, I led the rollout of an AI-powered pest detection platform across pine forests in Scotland and northern Europe. The target? A specific pest – the Large Pine Weevil (Hylobius abietis) – responsible for destroying ~8% of the UK’s pine forests each year. But like most real problems, it wasn’t just about the pest.

 Climate, Cost, and Carbon

The system on the ground was fragile. Forest managers were inspecting vast estates using diesel vehicles – often just once every two weeks. By then, the weevils had burrowed in and the trees were dying.

This wasn’t just a pest monitoring problem. It was a carbon-intensive, data-poor, labour-heavy infrastructure failure – one that conventional tools couldn’t solve.

Designing for the System, Not the Spec

We built a vision-based edge sensor combined with predictive ML models – capable of identifying pest activity in real time and correlating it with environmental factors like moisture and soil health.

But the key wasn’t just building smart tech. It was making it land.

Over six months, I met with more than 20 forest district managers across Scotland and England – not to pitch, but to listen. Their insights reshaped everything. Alerts matched existing treatment cycles. Dashboards focused on actionable metrics, not confidence scores. Carbon impact was baked in to support climate-linked funding.

That alignment turned interest into adoption. Within a year, we closed a $230K pilot, a $600K scale-up, and a $4M multi-year contract.

Lessons for Founders Working in the Wild

1. The edge isn’t just technical – it’s operational.
 Your device is competing with clipboards and pickup trucks, not other sensors. Design accordingly.

2. Serve the institution, not just the end user.
 If your product doesn’t align with system-wide KPIs – emissions, biodiversity, public reporting – it won’t scale, no matter how loved it is.

3. Translate your AI into decisions.
 Managers don’t want model outputs. They want to know: Do I need to act today?

Every layer of complexity you remove builds a layer of trust.

The Forest as a Prototype

This wasn’t just about saving trees. It became a template for scaling AI in climate-critical sectors – from water to agriculture to biodiversity.

In these systems, success doesn’t come from raw performance. It comes from fit – technical, cultural, and institutional.