Conversational AI

Power your conversational AI models with unique access to sensitive customer data

Fine-tune language models on federated data

Users expect seamless and flawless interactions. Integrating conversational AI into your products requires ML teams to fine-tune their language models to customer interactions. Leverage federated learning to access such sensitive customer data that spans across customers, systems or geographies.

Conversational AI

Telemedicine and patient apps

Train and evaluate language models on sensitive medical information and personal health data while protecting data privacy. Ensure models are explainable, predictable and trustworthy.


Collaborate with financial institutes and fine-tune ML models on sensitive customer data. Ensure that the data always stays protected and never leaves the financial institutes' environments.

Personalized advertisement

Gain an unbeatable competitive edge through the ability to leverage sensitive consumer data in a privacy-safe way. Build better and more accurate ad targeting models without moving or aggregating consumer data.

Why conversational AI teams choose Apheris

IP protection of data

Apheris federated infrastructure ensures that data always stays where it resides and under the full control of the data custodian.

Integrated SDK

ML engineers can easily launch their pre-trained language models from, for example, Huggingface and fine-tune them to sensitive data of third-parties.


The Apheris Platform scales to very large compute workloads as required for most conversational AI applications.


Apheris offers state-of-the art security, privacy and governance to ensure compliance across regulatory requirements.


"We need to launch our product on a federated infrastructure – where PII data stays where it is captured and doesn't have to move across borders – there is no other way forward for us."

CTO Top-30 AdTech company

Any data, any size, anywhere

Want to learn more about how Apheris can help you power your infrastructure with federated machine learning and analytics?
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Refine large language models to boost AI performance

Open AI's ChatGPT is very popular, yet not ready for enterprise adoption due to accuracy, security & privacy concerns. By refining large language models this can be tackled. For organizations that operate in a regulated space, federated learning can be used to train on distributed data to unlock value while maintaining privacy.

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