Agentic AI for the public sector.On your own infrastructure.

Lawful processing of citizen data, purpose limitation and control over where data is processed. How Operaide supports it: Apps and their data are stored on your infrastructure. For each step of an app you choose which AI model processes the data and where it runs, fully local if needed.

Transparency, documentation and human oversight. AI used to decide on access to public benefits counts as high-risk. How Operaide supports it: Step-by-step tracing, human approval steps, and Audits: an EU AI Act assessment for every app, including its risk class.

The BSI's standard for information security in public administration. How Operaide supports it: Operaide runs inside your own infrastructure and controls, so it becomes part of your existing security concept, with every run traced as evidence.

Risk management and incident reporting. Federal administration is in scope, states and municipalities depending on national law. How Operaide supports it: Runs inside your security perimeter, with SSO, roles and step-by-step tracing. You decide when updates are installed.

Yes. Operaide ships as a container and runs in your own data centre or at your IT service provider, also fully air-gapped with local AI models.

Your caseworkers. The app checks completeness and drafts the notice. The decision and the signature stay with people, and every step is traced.

A first version of a simple app runs within hours, a complete one within days, depending on the systems you connect. In the AI Bootcamp your teams build their first apps with us in five days and roll them out.

Yes. There is no connector catalogue to wait for: each connection is built for your system through REST or MCP, including ERP, CRM, EDI, portals, older and in-house systems. Connections are set up once in the platform, and your apps read and write through them with the access rights you set, without secrets in the code.

Only if you decide so. Operaide runs on your own infrastructure, and for each step of an app you choose the AI model: a local model on your own hardware for data that must not leave, or a frontier model in your cloud tenant. An app can also use a local model to remove personal data before anything reaches a cloud model. Every run is traced, so you can see which data went where.