Ennovria provides an AI‑driven high‑voltage DC software platform that replaces traditional AC power distribution in AI‑focused data centers, reducing conversion losses and simplifying power delivery to GPUs and batteries. The platform uses predictive load management, real‑time monitoring, and a digital‑twin environment to optimize efficiency, reliability, and deployment speed for hyperscale and HPC operators.
Funding
Funding not disclosed
Founders
Product
Problem
AI-driven data centers require extremely high power density and continuous uptime, but traditional AC power distribution incurs significant energy loss, complex hardware, and long deployment times tied to grid interconnections. These constraints limit scalability, increase operational costs, and hinder rapid rollout of next‑generation compute facilities.
Solution
Ennovria offers an intelligent high‑voltage DC (iHVDC) software platform that transforms power delivery for AI‑focused data centers. The solution replaces conventional AC conversion chains with a DC microgrid architecture, reducing I²R losses and simplifying power flow to native DC loads such as GPUs and batteries. Its control and decision layer uses AI‑driven optimization, predictive load management, and autonomous adjustments to maximize efficiency and reliability in real time. A digital‑twin simulation environment enables hardware‑in‑the‑loop testing and rapid design iteration, shortening deployment cycles and ensuring performance before physical build‑out. The platform is vendor‑agnostic, supporting multi‑supplier hardware and seamless integration with existing infrastructure while providing continuous software updates to accommodate evolving AI hardware.
Target Audience
Primary customers are hyperscale data center operators, cloud service providers, and high‑performance computing facilities building or upgrading AI‑intensive compute clusters.
Features
- High‑voltage DC distribution architecture that eliminates AC‑to‑DC conversion losses for ultra‑dense AI racks
- AI‑powered optimization engine for predictive load balancing, energy waste reduction, and cost‑aware operation
- Real‑time monitoring dashboard and digital twin that delivers operational analytics, fault prediction, and autonomous control
- Vendor‑agnostic models and algorithms enabling integration with diverse power hardware and seamless upgrades
- Modular, redundant design supporting on‑site generation (microgrids, batteries, diesel/gas turbines) for grid independence and rapid go‑live
- Continuous software updates that adapt to new power modules and AI hardware generations without hardware redesign