An enterprise AI worker platform for automating complex operational workflows with ongoing evaluation and human oversight.
HappyRobot is an enterprise AI worker platform for operating complex workflows across areas such as logistics, utilities, finance, insurance, manufacturing, retail, and telecommunications. Its agents perform work in business systems, use operational context gathered through task execution, and are evaluated throughout deployment and production. The platform combines agent workflows, governance, and operational interfaces so teams can monitor activity, handle exceptions, and refine performance.
Define machine-checkable standards for agent communication, tool use, and business outcomes such as resolution, containment, and escalation. Assign rule priorities and calibrate evaluations with positive and negative examples.
Run adversarial scenarios, manually specified tests, and regression tests derived from production failures to check agent behavior and expected tool calls before releases.
Sample live sessions for behavioral audits, track workflow node errors, and evaluate voice-session transcription, speech quality, conversation flow, acoustic conditions, and latency.
Track session outcomes, audit results, workflow errors, and custom variables with alerts for specified patterns. Human feedback on audit results can become calibration examples.
Build operational apps from templates with a code editor and live preview. Apps can access real-time and historical Context data, trigger workflow actions, log tickets, and manage escalations.
Describe desired tests or an operational interface in natural language; the platform can generate test suites or create and wire an app to Context data for review and refinement.
Automate workflows such as carrier sales and shipment tracking, while giving operations teams interfaces to inspect agent activity and act on exceptions.
Use agents in outage dispatch and field workflows, with governance rules and live monitoring for operational outcomes and workflow errors.
Handle customer-service workflows and use interfaces to review interactions, manage escalations, and refine agent behavior from audit feedback.
Apply agents to collections, settlement, or first notice of loss, with defined objectives and testing for business-specific scenarios.
Turn production failures into regression cases and compare workflow versions on defined metrics before broadly deploying changes.
Agents can be tested before deployment with adversarial, custom, and regression scenarios. In production, sampled sessions can be audited against behavioral and business rules, with monitoring for workflow errors and voice quality.
The platform provides templates, a code editor, live preview, and an AI copilot that can generate and revise apps from a description. Interfaces can use agent-produced Context data and trigger workflow actions.
A thumbs-up or thumbs-down on an audit result can be added as a calibration example for the relevant rule, helping subsequent evaluations reflect that judgment.
The website identifies workflows across logistics, utilities, airlines, finance, insurance, manufacturing, retail, and telecommunications, including tracking, dispatch, collections, claims intake, supplier onboarding, returns, and network provisioning.
Traffic data is for reference only.
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