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Secure Federated AI · Funded by the NIH
Train together. Keep your data home.

PangeaAgora lets multiple organizations jointly develop and train AI models without sharing raw data — each participant contributes to a shared model while sensitive data stays private and in place.

Fig. AgoraTrain together · data never leaves.
§ 01The problem

The best models need shared data — but sharing raw data is impossible.

In healthcare, defense, and finance, the data that would make models better is exactly the data that can never leave the building.

Agora resolves the tension: organizations train on their collective knowledge without any raw data changing hands.

§ 02Collective intelligence, private by designFederated
01
Federated training
Multiple organizations contribute to one shared model — coordinated, not centralized.
02
Data never leaves
Raw data stays private and in place. Only model improvements are shared — never records.
03
Encrypted aggregation
Even the shared model improvements are protected by homomorphic encryption — the central aggregator can combine them to strengthen the shared model, yet can never read or access any participant's contribution.
04
Collective intelligence
Every participant benefits from a model stronger than any could build alone.
§ 03Why Pangea

Security is the architecture, not a setting.

Agora is built from the ground up on novel federated methods and peer-reviewed science, funded by the NIH — so collaboration and privacy are guaranteed by design, not by policy.

Our approach →

Build better models — without sharing a single record.