Anish Narang

AI agents can reason well, but most products still break at autonomous multi-agent execution: coordinating specialists, paying for actions, enforcing limits, and proving what happened without constant human intervention. Actuate solves this with an agentic system where: A Planner agent decomposes a user request and coordinates specialists. Rider, Foodie, and EventBot execute domain tasks (research, browsing, event registration) and return structured outputs. Agent-to-agent/API actions run through a payment-aware execution loop (402 challenge -> pay -> retry) with minimal human involvement. Every run is streamed live and replayable, so behavior is inspectable end-to-end. What People Can Use It For Running real autonomous workflows that require multiple specialist agents. Delegating agent permissions safely while still letting agents transact. Monitoring live operations and replaying runs for debugging, demos, and audits. Handling failures (scope violations, budget exhaustion, revocation) with clear enforcement and recovery behavior. How It Makes Existing Tasks Easier and Safer Easier: orchestration, specialist execution, payment flow, and evidence are unified in one control plane. Safer: every request is policy-gated (identity, nonce, session, passport, scope, service, rate, budget, payment). More accountable: each action can be traced to payment proof and receipt artifacts. Where Kite AI Fits Kite is a major part of the system because it provides the rails that make this agentic model trustworthy: x402-style pay-per-action flows for autonomous calls On-chain passport/session identity for verifiable agent permissions On-chain receipt logging for settlement traceability So the product’s center is the agentic orchestration system, and Kite is the core infrastructure that makes that autonomy secure and economically operable.