Use case · AI agents

Give AI agents data they can verify before they act.

AI agents often depend on APIs, tools and structured data that change independently. Zorqelio gives agent builders a deterministic validation gate: define the expected JSON shape, validate each response, and let your application decide whether the agent should continue.

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Why data contracts matter in agent workflows

An agent can only reason reliably about the data it receives. If an API silently removes a field, changes a number to a string, or returns an unexpected value, downstream reasoning and tool calls may be affected. A versioned contract makes the expected structure explicit and testable.

A practical validation flow

Create a private workspace and a JSON Schema contract.
Before passing a tool result to the agent, call contract_validate with the contract ID, access token and payload.
Continue only when the result is ALLOW. On BLOCK, stop the workflow or route the issue for review.
Use immutable contract versions to review and reproduce changes.

Connect through MCP or your own integration

Zorqelio exposes contract and monitor operations as MCP tools. Your application can also send JSON to an authenticated push-monitor endpoint. This keeps the enforcement decision in your workflow rather than asking an LLM to guess whether a payload is valid.

Zorqelio is a validation and freshness layer, not an agent runtime, model host or autonomous repair service.

What Zorqelio does—and does not do

Zorqelio validates JSON that your own integration submits. It does not fetch arbitrary customer URLs, store submitted raw payloads, or guarantee that an upstream provider is available. Its freshness monitor detects missed submissions against an interval you configure.