Registry Plane
Unified registration for agents, MCP servers, tools, connectors, and external services.
Agentic and Analytical Orchestration
NoETL Automation
NoETL combines agent registry, MCP server registration, MCP tool discovery, connector management, and dynamic workflow execution in one control plane. It also acts as an analytical workspace orchestrator for streaming data pipelines, data catalog, data lineage, and data governance with capabilities similar to dbt and Airflow style orchestration.
Agent and MCP Registry
MCP Tool Discovery
Petri Net and Turing-Complete DSL
Agent Mesh Support
Agent Economy Support
Streaming Pipeline Orchestration
Data Catalog, Lineage, Governance
AI, Data, and Quantum Workflows
- Catalogize and register AI agents in one runtime catalog.
- Register MCP servers and discover MCP tools across environments.
- Register and discover external APIs, databases, queues, model endpoints, and connectors.
- Implement agents as NoETL DSL playbooks and run them as dynamic workflows.
- Coordinate agent mesh and agent economy interaction patterns with governance controls.
- Orchestrate streaming data pipelines and analytical workspaces with capabilities similar to dbt and Airflow style systems.
- Manage data catalog, data lineage, and data governance as first-class runtime concerns.
NoETL Core Modules
NoETL provides one cloud wrapper for registry, discovery, runtime execution, and message learning.
Discovery and Control Plane
Petri-net orchestration with policy enforcement, deterministic transitions, and runtime traceability.
Agent Runtime Plane
Turing-complete NoETL DSL playbooks for branching, loops, routing, and composition.
Analytical Workspace Plane
Streaming pipeline coordination, data catalog operations, lineage tracking, and governance workflows.
Compute Plane
CPU, GPU, and QPU workload orchestration in one operational model.
Message Learning Plane
Event-driven learning loop for optimization, recovery, recommendations, and continuous improvements.
Message Learning Diagram
Message learning operates as a continuous loop: discover available agents and tools, execute workflows, collect events, enrich semantic memory, and update future decisions for routing, retries, resource selection, and workspace orchestration.
This model supports agent mesh collaboration and agent economy interactions while keeping governance, lineage, and operational controls observable from one runtime control plane.
Read the message-learning designManaged Workload Domains
Agentic Runtime
Register, discover, and operate agents and MCP tooling under policy and observability constraints.
Analytical Workspace Orchestration
Coordinate streaming and batch data pipelines, data catalog workflows, lineage capture, and governance checks.
AI and Quantum Integration
Run inference, optimization, and QPU workloads in the same lifecycle as regular enterprise data flows.
Start on noetl.dev, Build with GitHub, Operate on noetl.ai
Learn concepts in docs, inspect implementation in the open-source repository, and use this domain as the public entry point for NoETL runtime capabilities.