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EnopAI Tech Stack

AI-driven optimization for energy management systems

Technology, Information and Internet München 2–10 employees Public Company
enopai.com LinkedIn

EnopAI builds optimization software for energy management, combining machine-learning forecasting with mathematical modeling to find economically optimal operating modes for power systems. The stack reveals a frontend-heavy architecture (React, TypeScript, D3.js, Recharts) paired with optimization engines (Pyomo, FastAPI), suggesting they're solving the hard problem of translating complex optimization logic into intuitive dashboards for operators. Senior hiring in engineering and data signals a focus on both modeling depth and product velocity.

Tech Stack 19 technologies

Core StackReact TypeScript Vue Svelte Python FastAPI Heroku AWS Figma Tailwind CSS Pandas GitHub D3.js Recharts GCP Pyomo asyncio SQLAlchemy

What EnopAI Is Building

◆Challenges

  • Black box ai optimization
  • Grid constraints
  • Tough frontend problems
  • Reducing carbon emissions
  • Optimizing energy assets
  • Complex energy optimization logic
  • Weather uncertainty
  • Market volatility
  • Reducing energy costs
  • Slow product iteration

▲Active Projects

  • Energy optimization product development
  • Advanced data visualization of live power flows
  • Hybrid energy system optimization models
  • Ems control logic design
  • Main web application
  • Dashboards and digital twin configurations
  • High-performance charting for live power flows
  • Interface and apis for optimization engine
  • Energy management system user experience design
  • Battery state interface design

Hiring Activity

Accelerating9 roles · 5 in 30d

Department

Engineering
5
Data
1
Design
1
Marketing
1
Product
1

Seniority

Senior
7
Intern
2
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About EnopAI

EnopAI develops optimization-as-a-service software for energy management systems. The platform integrates AI-based forecasting with mathematical optimization to generate operating recommendations tailored to individual power systems' constraints and economics. Core surfaces include live power-flow visualization, digital-twin dashboarding, battery state interfaces, and an optimization engine API. The company operates from Munich and currently serves energy operators seeking to reduce costs and carbon emissions while navigating weather uncertainty and volatile markets.

HeadquartersMünchen
Company Size2–10 employees
Hiring MarketsGermany

Frequently Asked Questions

What technology stack does EnopAI use?

Frontend: React, TypeScript, Vue, Svelte, D3.js, Recharts, Tailwind CSS. Backend: Python, FastAPI, Pyomo, Pandas, SQLAlchemy, asyncio. Infrastructure: AWS, GCP, Heroku. Design/collab: Figma, GitHub.

What is EnopAI working on?

Energy optimization product development, live power-flow visualization, hybrid energy system models, EMS control logic, web application, digital-twin dashboards, and optimization engine APIs. Current pain points include black-box AI transparency, grid constraints, and product iteration speed.

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