Data EngineeringRare
Used by 5 of 3.440 companies (0.1%)
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
Generative AIRare
Used by 8 of 3.440 companies (0.2%)
TensorFlowRare
Used by 28 of 3.440 companies (0.8%)
PyTorchRare
Used by 117 of 3.440 companies (3.4%)
Computer VisionRare
Used by 126 of 3.440 companies (3.7%)
NLPUncommon
Used by 184 of 3.440 companies (5.3%)
PythonCommon
Used by 1.317 of 3.440 companies (38.3%)
In context
Comparison data missing for this company — we'll add it on the next research run.
Similar companies
Similar companies
Similar stack
At least 2 shared technologies
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- Cancilico3 shared techsDresdenhealthtech / digital-pathologyPythonTensorFlowComputer VisionDigital Pathology
- CERPRO3 shared techsBerlinIndustrial SaaS / QA AIPythonPyTorchComputer VisionTypeScript
- Compredict3 shared techsDarmstadtAutomotive / AI / Software-Defined Vehicles / Virtual SensorsPythonTensorFlowPyTorchEdge-AI
- deeplify3 shared techsBochumAi / Industrial / DeeptechPythonPyTorchComputer VisionCloud-Stack
Same location
Local tech ecosystem
- Focused EnergyDarmstadtdeeptech / fusion energyLaser-FusionsphysikHPCSimulation
- Focuses EnergyDarmstadtdeeptech/energy/fusionLaser FusionHigh-Energy PhysicsSimulation
- WingcopterDarmstadtMobility / Drones / Logistics / DeeptechC++ROS 2PX4-Flight-StackPython
- CompredictDarmstadtAutomotive / AI / Software-Defined Vehicles / Virtual SensorsPythonTensorFlowPyTorchEdge-AI
- Compredict GmbHDarmstadtAI / Automotive / Predictive AnalyticsVirtual Sensor TechnologyML-ModelleEdge ComputingPython
- etalyticsDarmstadtcleantech / ai / energyPythonAIMLDigital Twins
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