Nvidia-backed ThinkLabs AI raises $28 million to tackle a growing power grid crunch

Nvidia-backed ThinkLabs AI raises  million to tackle a growing power grid crunch

Nvidia-backed ThinkLabs AI raises $28 million to tackle a growing power grid crunch

https://venturebeat.com/infrastructure/nvidia-backed-thinklabs-ai-raises-usd28-million-to-tackle-a-growing-power

Publish Date: 2026-03-31 06:00:00

Source Domain: venturebeat.com

  • Funding Announcement: ThinkLabs AI has raised $28 million in a Series A financing round, led by Energy Impact Partners (EIP) and joined by NVentures (Nvidia’s venture arm) and Edison International.
  • Purpose of Funding: The funding will assist ThinkLabs in scaling its AI models designed to simulate the behavior of electric grids, reducing the time required for complex simulations from weeks to minutes.
  • Competitive Edge: ThinkLabs emphasizes that their AI performs actual power flow analysis, contrasting with other AI applications that focus more on prediction or local energy management.
  • Strategic Partnerships: ThinkLabs has established important relationships with industry leaders like NVentures, Edison International, and Microsoft, enabling advanced grid simulation and integrating with utility infrastructure.
  • Utility Collaboration: ThinkLabs has demonstrated its capabilities via a successful project with Southern California Edison, showing significantly reduced analysis times compared to conventional tools.
  • Business Growth: The startup has seen a notable increase in utility clients, accelerating its sales cycles from a traditional one to two years down to two to three months.
  • Data Accuracy and Safety: ThinkLabs stresses high accuracy (99.7%) across critical planning studies and employs hybrid models blending AI with traditional physics-based simulations for real-time applications ensuring safety.
  • Future Vision: ThinkLabs envisions AI as a transformative force for modernizing grid operations, transitioning from reactive to proactive management and offering solutions like workload distribution and energy affordability.