Agentic AI for chemicals and pharma.On your own infrastructure.

Registration, classification and labelling of substances, and safety data sheets that stay current with every change. How Operaide supports it: Apps keep data sheets and declarations consistent with your product data. Experts approve every update, and each step is traced.

Computerised systems in GMP: validation, audit trails, access control and data integrity. How Operaide supports it: Apps versioned in Git, a step-by-step audit trail of every run, roles and SSO, and human approval steps.

Risk management, incident reporting and supply chain security. Chemical and pharmaceutical manufacturers are among the sectors in scope. How Operaide supports it: Runs inside your security perimeter, with SSO, roles and step-by-step tracing. You decide when updates are installed.

Transparency, documentation and human oversight for the AI systems you use. How Operaide supports it: Step-by-step tracing of every run, human approval steps, and Audits: an EU AI Act assessment for every app.

Yes, with the right controls: the app prepares, a qualified person decides, and every run is traced, versioned and approved. Whether an app needs validation depends on its GMP relevance, and we support you with the documentation.

They draft data sheets and translations from your approved phrases and product data. A product safety expert checks and releases every version.

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.