Sensor Data ProcessingRare
Used by 1 of 3.440 companies (0.0%)
startup
Alcemy
- Location
- Berlin· Berlin
- Industry
- cleantech / ai
- Founded
- 2018
- Employees
- 51-200
- Total funding
- €15.0 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
Predictive AnalyticsRare
Used by 7 of 3.440 companies (0.2%)
IoTUncommon
Used by 241 of 3.440 companies (7.0%)
MLUncommon
Used by 447 of 3.440 companies (13.0%)
AIUncommon
Used by 465 of 3.440 companies (13.5%)
PythonCommon
Used by 1.317 of 3.440 companies (38.3%)
In context
Raw numbers say little — here's how Alcemy compares to its industry and city.
Funding position
Top 39%
More funding than 61% of all companies with reported funding.
Industry median: €1.0 Mio
Industry peers
6
6 companies in the same industry
1 of those in Berlin
Similar companies
Similar companies
Same industry
Competitors and peers
- InvertixMünchencleantech / aiAIMLIoTRenewable Energy Operations
- InnoCharge GmbHKarlsruhecleantech / aiAIMLEnergy AnalyticsPython
- Path to ZeroKarlsruhecleantech / aiAIMLDecision IntelligenceData Analytics
- Invertix AI GmbHMünchencleantech / aiPythonAIMLLLM
- MaxxWattBerlincleantech / aiPythonKIMLIoT
- OptocycleTübingencleantech / aiComputer VisionPythonAIML
Similar stack
At least 2 shared technologies
- etalytics5 shared techsDarmstadtcleantech / ai / energyPythonAIMLDigital Twins
- aiomatic (ai-omatic solutions GmbH)4 shared techsHamburgai / industrialtechPythonAIMLPredictive Maintenance
- CleverSolutions Autonomous4 shared techsBerlinmobility/autonomousPythonCloudFleet ManagementAI
- Datagon4 shared techsMünchenai / manufacturing / qualityPythonReinforcement LearningAIML
- embee4 shared techsBonnenergytech / aiPythonAIMLData Analytics
- GALVANY (Galvany Energy GmbH)4 shared techsBerlincleantech / energyReactNode.jsPythonAI
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