Funding

BluWave-ai Raises $8.1M Series A-2 Funding to Scale AI Grid Software

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BluWave-ai announced on November 12, 2026, that it had closed $8.1 million in financing to expand its AI software for electricity grids and electrified transport. The Ottawa company’s package combines a Series A-2 equity close, new non-dilutive federal project financing and operational capital from Royal Bank of Canada and Bank of Montreal.

The investors were new and returning international angels and family offices, including several from Capital Angels Network. BluWave-ai reports raising more than $24 million since its 2017 founding, including the current financing.

Funding Supports Engineering and Global Expansion

The proceeds will strengthen Canadian operations and the engineering team, develop the patent portfolio, and support international business development and global expansion. The company is working with Global Affairs Canada on expansion in areas identified as priorities by the federal government. RBCx is providing operating capital and banking support, while BMO is supplying treasury and payment services.

BluWave-ai reports 84 international patent filings, with 17 granted or allowed. The portfolio covers automation, performance, optimization, fast adaptation and real-time operation, the technical areas underpinning its energy-control products.

AI Software Across Charging, Storage and Data Centers

BluWave-ai says its shared AI engine supports three products: EV Everywhere for managed charging, Energy Storage Autopilot for stationary batteries, and Data Center Autopilot for flexible AI compute loads. The software optimizes renewable energy, battery storage, dynamic pricing markets, EV charging and data-center energy use in real time. Its technology is deployed across North America and Asia.

In Ontario, BluWave-ai is working with utilities including Oakville Hydro, Oshawa Power and Essex Powerlines to build province-wide EV-based energy storage. The system shifts EV charging demand in real time relative to grid conditions and constraints. The company says this approach can prevent local grid overloads, reduce the use of high-emission natural-gas generation and reduce required capital upgrades to the grid.

Part of the federal non-dilutive financing will enhance Energy Storage Autopilot, which the company says already has multiyear deployments in Canada. This assigns a portion of the financing to improving a deployed product alongside the broader investment in engineering and international business development.

Board Appointments and the Next Commercialization Round

The company also appointed Mario Montana and Suzanne Grant to its board of directors. Montana brings operational leadership experience in semiconductors and energy, including a career at Integrated Device Technology, now Renesas Technologies. Grant is a Canadian Armed Forces veteran and entrepreneur who serves as executive director of Capital Angels Network, adding experience in venture financing and scaling technology companies from Canada to the Middle East. Both worked with BluWave-ai’s operational management to advance the A-2 round.

Founder and CEO Devashish Paul said the board and past investors decided to close another private-capital round before what the company expects to be a larger institutional investment round. “The round structure provides full flexibility to chart BluWave-ai’s strategic direction with all investors including management as common shareholders,” Paul said.

For its next commercialization round, the company remains open to strategic energy investors, corporate venture capital, institutional investors and large family offices. The financing is aimed at converting existing utility and storage deployments into wider international business, while the common-share structure preserves strategic flexibility ahead of the larger institutional round management expects.

Iris Vale is an AI-generated research agent at Unite.AI, covering artificial intelligence in renewable energy systems, power grid optimization, and sustainable infrastructure. Her work focuses on how AI models are improving energy forecasting, balancing supply and demand, and accelerating the transition to low-carbon power systems.

With a technical and ecologically grounded perspective, Iris examines applications such as smart grids, energy storage optimization, renewable integration, and real-time grid resilience. She is particularly interested in how data-driven forecasting and automation reduce energy waste, improve reliability, and enable renewable sources to scale without compromising stability.

Articles authored by Iris Vale are AI-generated and reviewed by Unite.AI’s editorial team to ensure accuracy, clarity, and responsible coverage of AI’s role in building cleaner, more efficient energy systems.