AI-native public health systems without centralized data

Public health depends on timely, accurate data, but that data is fragmented across local and state systems and is often too sensitive to share. Onai enables agencies to collaborate and analyze data together using advanced AI, while keeping data private and under their control.

The problem

Public health systems are inherently distributed

Local and state agencies collect critical data on disease, outcomes, and populations, but this data is siloed across jurisdictions, systems, and formats.

To act effectively, agencies need to combine data across regions, analyze trends in real time, and coordinate responses across organizations.

Today, doing this typically requires centralizing data, introducing delays, operational complexity, and significant privacy concerns.

As a result, investigations are slower, insights are limited, and collaboration is harder than it should be.

Data is fragmented across jurisdictions

Critical public health information is spread across local and state systems rather than available through one coordinated view.

Real-time action is difficult

Trend analysis and coordinated response are slowed down when teams cannot work across data sources quickly.

Centralization creates risk

Pooling sensitive records introduces delay, operational overhead, and privacy concerns at exactly the moment agencies need speed.

Our approach

Keep data where it is. Make it usable everywhere

Onai enables public health data to remain within the systems and jurisdictions that collect it, while still being used collectively through AI.

Data stays local to each agency. AI-powered computation runs across distributed systems. Insights are shared without exposing underlying records.

This allows agencies to function as a coordinated, intelligent network without requiring a central data repository.

Local data control

Each agency retains custody of the data it collects and governs.

Distributed AI computation

Queries and AI-assisted analysis run across the network instead of depending on a single centralized system.

Shared insight without raw exposure

Agencies receive useful outputs and coordinated intelligence without revealing sensitive underlying records.

What this enables

A more capable public health network

Investigations

AI-assisted investigations

Investigators gain access to AI tools that accelerate querying, case analysis, and decision-making without exposing sensitive data or relying on centralized systems.

Insight

Stronger epidemiological insight

Epidemiologists can analyze trends across jurisdictions using effectively unified datasets, unlocking deeper and more timely understanding of population health.

Collaboration

Real collaboration across agencies

Local and state departments can work together seamlessly without needing to standardize or centralize their underlying data systems.

System in practice

AI-powered, distributed public health infrastructure

Onai powers Guardian, a system designed to enable secure, AI-driven public health workflows across jurisdictions.

Guardian operates as a distributed network: each agency retains control of its own data, AI models and queries operate across the network, and insights are generated without exposing sensitive records.

This architecture enables a new model of public health, one that is faster, more intelligent, and privacy-preserving by design.

Control

Each agency keeps its own data

Guardian is built so agencies participate in the network without giving up jurisdictional control.

Intelligence

Queries and models operate across the network

AI workflows can span distributed systems while respecting the boundaries of each contributing organization.

Insight

Results are generated without exposing records

Agencies can act on shared intelligence without creating a central repository of sensitive data.

Visualization

A shared intelligence layer across agencies

A network visualization shows distributed public health agencies as nodes connected through a shared intelligence layer. Data remains local while computation and insight flow across the network.

Who this is for

Built for teams responsible for population-level response

Public health agencies

Local and state departments that need to collaborate, share insight, and respond quickly without compromising confidentiality.

Investigators

Teams conducting case investigations who benefit from AI-assisted workflows and faster access to relevant information.

Epidemiologists

Researchers and analysts who need to understand population-level trends across fragmented data sources.

A public health system for today's world

Onai enables agencies to operate as a connected, AI-powered network, improving speed, insight, and outcomes while preserving trust.