AI in clinical interfaces

Use AI applications and language models in clinical interfaces.

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Expose a clinical lookup as a tool and an AI agent answers 'did the admission arrive?' end to end.

Expose services as MCP

Agents answering your questions

Expose services as MCP Let AI applications use existing Zato services under the access controls you define. Interface health Review recorded HL7 failures across interfaces in one result. Feed silence Report interfaces whose latest message exceeds a silence threshold. Tool schemas Derive the tool definition from a service's docstring and declared fields.

Your services calling models

Calling LLMs from clinical services Invoke a model from a clinical service in one line of Python. Self-hosted models Point the same service at Ollama, vLLM or a corporate model gateway. Cost and limits Every response reports its token usage and configurable limits cap what an interface may spend.

Safeguards on patient data

MCP gateway security Every gateway requires authentication, and separate credentials provide separate client identities. Response controls Configure PII detectors, content safeguards and size limits for tool responses. Rate limits Attach rate rules to credentials to limit clients independently. MCP audit log Record payload-free metadata for handled MCP requests, including their callers, outcomes and sizes.