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We develop ML that optimizes how batteries in the grid store energy
Founded in 2022, Atmeto was started as a place to develop and apply machine learning to solve the world's biggest problem—climate change. Our current priority is getting the grid to run on 100% clean energy, which is currently limited by battery storage (specifically, the algorithms that control them). We're redefining these algorithms to unlock gigawatts of untapped energy storage capacity, enabling the grid to run on more clean energy from wind and solar.
Atmeto develops machine learning technology to optimize how batteries store energy for the grid as part of the clean energy transition. The company positions itself at the intersection of ML and energy generation to decouple carbon emissions from energy production.
The product uses artificial intelligence to optimize battery storage operations within grid-scale energy systems, aiming to improve efficiency and performance of energy storage deployments.
Who it’s for: Utility-scale energy developers, grid operators, energy storage project developers, clean energy companies needing optimized battery storage solutions
backed by YC and several investors; team with industry and research background
I build Reinforcement Learning for energy systems. Currently building Atmeto (f.k.a. Keeling Labs). Previously at Rivian for 3+ years building battery data science from the ground up, where I ultimately focused on applied AI (RL) for battery optimization in R1T/R1S.
We help grid-scale battery operators adapt to changes in the grid with energy management software that automatically adjusts its behavior to maximize revenue
Keeling Labs provides energy management software for grid-scale battery assets, using reinforcement learning to autonomously optimize when to buy and sell power. The product targets asset owners and utilities to improve asset returns amid dynamic grid prices.
From the original launch (Jan 2023) — may be outdated.
Formerly “Keeling Labs” · why startups rename →
