[Digital-Twin-Simulations-Engine (proprietär)Rare
Used by 1 of 3.440 companies (0.0%)
startupVerified
Re-Twin Energy GmbH
- Location
- Berlin· Berlin
- Industry
- energy / ai / digital-twins / battery-optimization
- Founded
- 2025
- Employees
- 11-50 (~13)
- Total funding
- €2.0 Mio
Tech-Stack
Tech stack in context
Each entry is benchmarked against all 3.440 companies in the dataset. Rare items first — those are the more interesting choices.
RareUncommonCommonMainstream
PyTorch für Storage-Profitability-ModelleRare
Used by 1 of 3.440 companies (0.0%)
PandasRare
Used by 1 of 3.440 companies (0.0%)
Energy-Market-APIs (EPEXRare
Used by 1 of 3.440 companies (0.0%)
EEX)]Rare
Used by 1 of 3.440 companies (0.0%)
Scikit-LearnRare
Used by 3 of 3.440 companies (0.1%)
React-DashboardRare
Used by 4 of 3.440 companies (0.1%)
Cloud (AWS)Rare
Used by 12 of 3.440 companies (0.3%)
TypeScriptUncommon
Used by 451 of 3.440 companies (13.1%)
PythonCommon
Used by 1.317 of 3.440 companies (38.3%)
In context
Raw numbers say little — here's how Re-Twin Energy GmbH compares to its industry and city.
Funding position
Top 85%
More funding than 15% of all companies with reported funding.
Industry median: €2.0 Mio
Similar companies
Similar companies
Similar stack
At least 2 shared technologies
- AGVOLUTION GmbH3 shared techsGöttingenagtech / precision-farming / soil-sensorik / ai-fertilization[proprietäre CLIMAVI-Sensorik (BodenfeuchteTemperaturMikroklima über 3 Tiefen)LoRaWAN
- Credibur3 shared techsBerlinFinTech / Private Credit InfrastructureTypeScriptPythonCloud (AWS)API-first
- Kaiko Systems GmbH3 shared techsBerlinmaritime-tech / industrial-iot / ai-inspection[Mobile-First (SwiftKotlin)TypeScriptReact-Dashboard
- lemon.markets3 shared techsBerlinFinTech / Brokerage-API / Embedded InvestingPythonTypeScriptREST APIsCloud (AWS)
- paretos3 shared techsMannheimsaas / ai (Decision Intelligence)PythonPyTorchScikit-LearnAWS
- Phase03 shared techsBerlinAI / Architecture SaaS / Feasibility AnalysisPythonTypeScriptReactML
Same location
Local tech ecosystem
Consulting on this stack
Working with a similar stack?
We help companies like this build data-driven platforms — from AI research to production deploy.
Reuse & citation
How to cite this dataset
TechPuls is published under CC BY 4.0 — free to use, including commercially, as long as the source is credited. Here is a ready-made line for that.
Citation
Techlogia (2026). TechPuls Germany — Dataset of the German tech landscape. 3,440 companies in 245 cities. Licensed under CC BY 4.0. Available at https://techlogia.de/en/techpuls
BibTeX
@misc{techpuls,
author = {Techlogia},
title = {TechPuls Germany — Dataset of the German tech landscape},
year = {2026},
howpublished = {Online-Datensatz},
note = {CC BY 4.0},
url = {https://techlogia.de/en/techpuls}
}- Data as of
- Machine-readable access
- The same data is available as JSON via the open API — no key, no registration: /api/techpuls/cities
- Licence terms:
- CC BY 4.0