The layer that connects one system to another.
Pravadh MW sits between your systems — translating data, managing requests, and repairing itself when schemas drift. An agent builds the flow from live schemas; a human still approves every patch.
Four jobs, one middleware layer
Whatever's on either side of the wire — an internal API, a legacy system, a SaaS product — Pravadh MW sits in between and does the work neither side should have to.
One format in, another out
Converts between formats — XML to JSON and back, and field-level mappings beyond that — so systems that don't speak the same language understand each other.
Requests, queues, streams
Manages requests and responses, message queues, and asynchronous data streaming between separate services.
Gatekeeper before the backend
Handles authentication, authorization, and encryption of data in flight, before a request ever reaches a backend database.
Error handling & observability
Catches and logs failures instead of dropping them silently, with retry and healing loops when the target drifts.
Why Pravadh MW does it differently
Traditional middleware makes you draw the mapping on a canvas and hope it survives the next API change. Pravadh MW is built agent-native from the ground up.
Describe it, get a flow
Tell the agent what you want connected. It reads both systems' live schemas and proposes the field mapping as a reviewable file.
Drift doesn't break runs
Every run re-introspects the target schema first. On drift, a patch is proposed automatically and held for approval before anything writes.
Your repo is the source of truth
Flows are pydantic-validated YAML plus ordinary Python connectors. Diff them, review them, roll them back like any other code.
The LLM proposes, never executes
Repair proposals come from an LLM; the engine that reads, translates, and writes your data never calls one. Predictable, auditable runs every time.
How it works
Three steps between "we need this connected" and a running, self-monitoring flow.
Describe the integration
Point Pravadh MW at a source and target connector. The agent introspects both live schemas and proposes a field-level mapping.
Review and approve
Every proposed flow — and every later drift patch — is a plain-text diff. Nothing runs against your systems without a human approving it.
Run, and keep running
The engine executes on demand, re-validating the target schema every time and healing itself when the shape changes underneath it.