Battery analytics and state estimation for electric vehicle fleets
Coulomb AI builds analytics and optimization software for EV battery performance. The tech stack (React + Next.js frontend, Python + Flask backend, PostgreSQL + Redis for state, AWS/GCP infrastructure) and active projects reveal a company focused on real-time battery monitoring: state estimation, thermal management, energy demand forecasting, and reinforcement learning for charging strategies. The senior-weighted engineering team (4 of 5 engineers at senior level) working on mission-critical analytics and observability platforms suggests they're solving deep technical problems in battery telemetry and fleet optimization rather than selling a simple dashboard.
Coulomb AI develops a battery analytics platform for electric vehicle fleet operators and OEMs. The product centers on real-time monitoring and optimization: battery state estimation algorithms, energy demand forecasting, thermal management, and ML-driven charging strategies. The platform ingests live fleet data via scalable APIs and ETL pipelines, surfaces insights through real-time dashboards and alerts, and exposes analytics via a SaaS interface. Founded in 2021, the company is a small, India-based team with engineering-first structure and accelerating hiring velocity focused on both backend systems and design.
Frontend: React, Next.js, Redux. Backend: Python (Flask, Django), Java. Data: PostgreSQL, MySQL, Redis, Pandas, Polars. Infrastructure: AWS, GCP. Design: Figma, Sketch, Adobe XD.
Battery state estimation, energy demand forecasting, thermal optimization, reinforcement learning for charging, real-time analytics dashboards, ETL pipelines, scalable APIs, and battery observability platforms.
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Coulomb AI's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
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