Katulu Platform
AI without sharing data for industrySolve your customers' core problems that are too big to solve alone with our platform. Do this by scaling your AI models for each use case across enterprise boundaries without sharing data. Benefit from data-sovereign MLOps, highly scalable edge management, and of course production-ready Federated Learning (FL).

The data you need from other stakeholders is inaccessible?! Not anymore!
Companies do not want to share their data. This is a fundamental problem with the use of AI in industry. The reasons and limitations for this are many and justified.
- Strategic constraints are ubiquitous in industry. Companies want to protect their knowledge so as not to jeopardize their competitiveness.
- Legal restrictions particularly concern the use of personal data, but also information relevant to the stock exchange.
- Technical restrictions such as lack of connectivity can usually be solved technically. However, they are often not resolved for economic or strategic reasons.
But what if sharing data is not required for using data?
Advantages
Solve problems you can't solve alone.
Solve central problems of your industry together with your customers and partners - from circular economy to cost efficiency in global competition.
Leverage data you'll never get access to.
Train more robust and accurate models at your customers' sites, without the data leaving their premises. Learn together with your customers without learning about them thanks to federated learning.
Optimize the entire ML lifecycle.
Automate and scale MLOps and industrial edge management for all your customers to manage and optimize models and infrastructure at large scale across company boundaries.

Are you unsure if our platform fits to your needs?
Let's talk about your use case. I look forward to hearing from you.
+49 (0) 40 / 22 86 03 19 - 2High-Performance, Data Sovereign & Cost-Effective.
The Katulu Platform has been built based on long lasting experience by domain experts from industry for industry und is the benchmark for Federated Learning in the industry.
Machines integrable
Larger Data Foundation
Higher Probability of Success
Clients per Training Cycle
Increased Reliability
Lower Total Cost of Ownership (TCO)
A Unique Solution
Compare our platform with other machine learning (ML) and federated learning (FL) solutions. Learn about the features for your success.
Katulu Platfoem | Central ML (e.g. AWS SageMaker) | OtherĀ FL Options | |
---|---|---|---|
General | |||
Designed for the Industry | |||
Production-Ready | |||
Open Source | |||
Federated Learning | |||
Horizontal Federated Learning | |||
Vertical Federated Learning | |||
Clustered Federated Learning | |||
Data Science | |||
Python SDK | |||
Federated Analytics | |||
ML Framework Agnostic | |||
Privacy | |||
No Transfer of Customer data | |||
Built-in Differential Privacy | |||
Privacy Wizard | |||
Infrastructure | |||
Highly scalable MLOps | |||
Industrial Edge Management | |||
Cloud-agnostic by Design | |||
Fully managed Enterprise SaaS | |||
Managed Service in your Cloud |
Our platform supports all leading ML frameworks & toolkits



