Expose durable workflows through APIs so your product can trigger multi-step research, validation, and delivery while AgentRuntime manages tools, state, intervention, and observability behind the interface.
This page describes a reference execution path built from documented AgentRuntime and connector capabilities. It is not a customer case study or a claim about measured performance.
Your application sends a typed workflow request with user context, input payload, and response delivery preferences. The graph then carries the same run through every typed step, human checkpoint, and outcome below.
Create a durable run from a workflow API request and retain the caller, request identifier, and input payload.
Hand the request to AgentRuntime and persist the returned run identifier as workflow state.
Execute approved research and extraction tools in parallel while retaining each tool response on the run timeline.
Combine tool outputs into a single candidate response that matches the product schema and policy constraints.
Apply explicit schema, safety, and confidence rules before the result is returned to the product.
Deliver the approved response through the configured stream or callback channel with the run reference attached.
Create a durable run from a workflow API request and retain the caller, request identifier, and input payload.
Hand the request to AgentRuntime and persist the returned run identifier as workflow state.
Execute approved research and extraction tools in parallel while retaining each tool response on the run timeline.
View integration details →Combine tool outputs into a single candidate response that matches the product schema and policy constraints.
View integration details →Apply explicit schema, safety, and confidence rules before the result is returned to the product.
Deliver the approved response through the configured stream or callback channel with the run reference attached.
Publish the final status and retain the request, tool calls, validation decision, and delivery trace on one timeline.
The starter graph makes human responsibility and error recovery visible instead of hiding them in a long prompt or chat thread.
Sensitive or policy-bound requests can pause for operator review before external tools execute.
Invalid or low-confidence outputs route to fallback logic or human review instead of reaching the product.
The platform confirms the product received the final payload before the run is marked complete.
Retain the failed step, apply retry policy, and continue with partial context when the workflow allows it.
Route the run to fallback generation or human review while preserving the rejected candidate on the timeline.
Keep the run in a visible wait state, retry delivery, and surface the failure for operator intervention.
The blueprint links to the integrations used in this path. Confirm workspace access, scopes, and environment configuration before the workflow acts.
Bring the trigger, integration boundaries, authority rules, and actions your team is willing to automate. We will map the production path and its controls.
