Workload demand
Product experiences and external applications create demand without defining the limits of the network.
Tenzarch is a Decentralized AI Execution Network. It connects AI workload demand with distributed execution infrastructure while preserving execution identity, orchestration, routing, operational visibility, and result delivery.
Users, applications, AI Agents, and developer integrations can originate AI workloads. Tenzarch accepts those workloads into a shared execution model, records them as Execution Jobs, coordinates them through Workflow Runs, routes them toward eligible capacity, and returns structured results to the originating surface.
Product experiences and external applications create demand without defining the limits of the network.
Jobs, Workflow Runs, lifecycle state, routing, assignment, and retries make execution explicit.
Execution Nodes provide processing capacity that can become eligible for assignment.
Status, timestamps, logs, telemetry, assignment, failures, and results make execution inspectable.
User-facing AI experiences that submit workloads.
Reusable developer-facing execution capabilities.
The coordination layer connecting demand, state, orchestration, routing, infrastructure, and results.
Usage accounting for execution.
A wallet-associated entry point into node participation.
A separate participation program for qualifying node activity.
Understand the network layers and execution boundaries.
Learn queued, routing, assigned, running, completed, failed, and retrying states.
Understand AI Agents and AI Executions as workload sources.
Understand Execution Nodes, eligibility, assignment, and Free Execution Node participation.
Integrate through scoped API Keys, idempotent submission, Jobs, logs, telemetry, and credits.