Every receipt checked, not a sample.Against your travel and expense policy.

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.

Only where you allow it. Typically it books clean matches within your tolerances, and your finance team releases the rest and decides on differences. Every step is traced, so you can show who released what.

Only where you allow it. The app checks and flags, and your team decides on the deviations. For clear cases you can let it approve automatically, and every step is logged.

Domain experts build no-code in the App Builder, and developers extend the apps in code in Operaide Studio. IT keeps control of AI models, data and access. If you like, our engineers build the first version with you, for example in the AI Bootcamp.

Commercial, European and self-hosted AI models: OpenAI, Anthropic, Mistral, Azure, Google, Amazon Bedrock, OpenRouter and more, or open-source models via Ollama or LM Studio. Your administrators configure them, and every step of an app can use its own AI model, chosen for its task.

Yes. The apps read emails, PDFs, Word and Excel files, scans, faxes and photos, including tables, handwriting and stamps. How well depends on the AI model behind the task, and today's models are very good at it. Documents the app is not sure about are flagged for a person to check.

They go to a person, marked as unclear. You decide where the app works on its own and where it asks for a check. Your team's decision can become a new rule for next time, and every step is traced.