Eclipse Ventures leads $22 million Series A in QueueGrid to ease AI data center interconnection bottlenecks

QueueGrid, a San Francisco startup that models utility interconnection timelines for large power users, raised a $22 million Series A led by Eclipse Ventures on Monday. The company sells planning software to utilities and data center developers, aiming to shorten multi year waits for new capacity that have intensified with the rise of AI training clusters.

The round underscores how venture investors are rotating capital from model labs into power and infrastructure as shortages of grid capacity slow rollout plans. Interconnection queues have grown across regions, and developers cite opaque upgrade requirements and unpredictable timelines as a primary constraint on siting.

QueueGrid’s platform ingests utility planning data, transmission constraints, and substation upgrade roadmaps, then runs scenarios that estimate cost and time to energization for specific sites. The tool targets site selection teams at hyperscalers and co location providers, and planning groups at investor owned and municipal utilities. The company says it can surface feasible feeders and quantify the tradeoffs across grid upgrades versus on site generation.

Eclipse Ventures has leaned into industrial and supply chain software, and its participation signals a continued push into power infrastructure tied to compute demand. The firm is betting that software that reduces friction in regulated workflows can convert into durable contracts, even if sales cycles run longer than typical SaaS.

QueueGrid reports early pilots with several utilities and regional transmission participants, along with paid evaluations by data center developers that are scouting secondary markets. The business model blends annual licenses with services for data normalization, which can lift initial contract values but requires heavier onboarding.

The timing matters because hyperscalers and AI startups are competing for megawatts in markets that are already capacity constrained. Utilities are under pressure to plan upgrades faster, while regulators weigh reforms to speed interconnection studies and cost allocation, creating a near term window for tools that quantify grid tradeoffs for both sides.

If investors keep shifting toward power aware compute, startups that marry utility grade data with siting economics will attract more early stage dollars. The winners are likely to be those that can prove accuracy against utility studies, withstand procurement scrutiny, and anchor into the broader stack of data center development software.