Stamford Startup Novele Raised $17 Million in Funding

The energy management company plans to use the capital to support its national expansion efforts.

Updated on Sept. 30, 2026 in Startups

Stamford Startup Novele Raised $17 Million in Funding

Live Poll

Is now a good time for building owners to invest in automated energy management systems?

Stamford-based Novele has raised $17 million in a Series A funding round led by Boisei Labs. The company, which provides energy management systems for commercial buildings, will use the investment to scale operations nationally.

Why it matters

The funding will allow Novele to expand its engineering, deployment, and commercial teams to support a growing pipeline of energy storage and software installations. This move marks a transition from its regional focus in the mid-Atlantic to a nationwide service model.

Novele has secured $17 million in a Series A round to support its current engagement with 2,000 buildings. The company manages a total pipeline spanning 2.6 billion square feet.

The players

Novele

A Stamford-based company providing energy management systems for commercial buildings through software and hardware integration.

Boisei Labs

An investment firm that led the recent $17 million Series A funding round for Novele.

The details

Novele offers a platform integrating BoardOS energy software with wall-mounted EnergyBoard hardware. The system utilizes proprietary algorithms to analyze consumption patterns by accounting for external variables like weather and occupancy.

2015: Novele was founded.
2023: The company was relaunched.
September 2026: Novele announced the Series A funding round.

Market Landscape

Novele's expansion mirrors the broader industry shift toward AI-integrated building management to meet sustainability goals. By scaling its proprietary hardware and software, the company is positioning itself to compete with established commercial building automation providers.

Commercial property managers and tenants may see improved energy efficiency and reduced utility costs as the company scales its hardware installations. These improvements rely on the system's automated learning to adjust energy use based on real-time occupancy and weather conditions.

The takeaway

Novele demonstrates how AI-driven algorithms can transform traditional building management into a dynamic energy storage solution. Businesses looking to lower their operational overhead should prioritize technologies that automate consumption patterns based on external data.