Clarity through truth.
52 operators · 65 MCP tools · One calm system.
Zenvara is an AI-native automation platform. It runs pipelines defined in YAML — as a single binary, on-premise — and treats every connector, every database, and every LLM call as the same kind of step.
It's one platform for three jobs that companies usually buy three platforms for:
- Data integration — ETL, joins, deltas, pagination, retries
- Service integration — HTTP, SOAP/WSDL, GraphQL, SFTP, S3, Kafka, and every major SQL & NoSQL database
- AI workflows — Claude, ChatGPT, and Gemini as native pipeline steps
Pipelines are written in YAML, but they are compiled to a typed AST before they run. Mistakes surface at validation, not at 3 a.m. Every write operator carries a compensating action, so failed runs roll themselves back. Every flow, call, and decision is logged and queryable.
It ships as a single binary. No JVM. No Python. No cluster required.
| AI as a pipeline step | Claude, ChatGPT, and Gemini are first-class operators — not plugins or wrappers. |
| Compiled, validated YAML | Type-checked references, expressions, and operator inputs before invocation. |
| Built-in rollback | Saga compensation per operator — successful writes know how to undo themselves on later failure. |
| Stateful pipelines | Cursors, deltas, and persisted variables work out of the box. No external database needed. |
| Native MCP server | The platform exposes itself to AI agents through 65 tools — discover, invoke, manage, and reason about every flow. |
| Self-introspecting | Annotations, context, and audit trails are part of the architecture, not bolted on. |
Define. Compile. Invoke.