Autonomy, the pioneering platform-as-a-service (PaaS) designed exclusively for agentic AI products, announced the general availability of its platform. This launch directly addresses the critical challenges developers encounter when transitioning autonomous agents from prototypes to production-ready solutions.

As businesses accelerate their adoption of “Software 3.0” and multi-agent AI systems powered by the Model Context Protocol (MCP), they often face recurring obstacles: complex integrations, governance gaps between agents, fragile workflows, high infrastructure costs, and limited visibility into agent behavior. Autonomy eliminates these barriers, allowing teams to deliver fully functional products instead of fragile demos.

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“Developers shouldn’t have to stitch together dozens of tools just to get an agentic product to run at scale,” said Matthew Gregory, CEO and Founder of Autonomy. “With Autonomy, every agent has a cryptographic identity, memory, knowledge, and safe tool integrations. Developers can deploy in seconds and scale to millions of agents without losing security or observability.”

Autonomy provides a comprehensive framework for building agents. Its open-source SDK allows developers to write agents in Python, connect them to tools via MCP or APIs, and deploy them directly to the Autonomy Computer platform. This setup ensures secure connectivity, elastic scaling, and built-in governance, removing the need to manage complex infrastructure.

Standalone agents running on a single laptop are insufficient for real-world applications. The true potential emerges when agents are orchestrated, deployed at scale, and integrated with enterprise systems. Autonomy Computer delivers the trust, governance, and interoperability necessary to transform individual agents into viable, customer-facing services.

The platform also offers superior runtime performance. Unlike container-based stacks, Autonomy Computer’s elastic actor runtime can simultaneously launch millions of lightweight, stateful agents. Cold starts occur in milliseconds, and workflows that once took hours now complete in seconds. Teams can begin with a proof-of-concept customer and scale effortlessly to enterprise-ready, multi-tenant solutions without re-architecting.

Secure connectivity at scale is another standout feature. Autonomy Private Links and identity-driven cryptography enable agents to connect across services with end-to-end encryption and mutual authentication, helping enterprises meet compliance requirements without reinventing security.

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Key capabilities include:

  • Framework & SDK – Rapidly build and deploy Python agents.
  • Secure connectivity & identity – Each agent possesses a cryptographic identity, while Private Links manage cross-cloud API and data access.
  • Elastic actor runtime – Run millions of agents with sub-millisecond cold starts.
  • Governance & isolation – Enforce least-privilege access via scope isolation and ABAC.
  • Observability & operations tools – Comprehensive logs, metrics, evaluations, and endpoints.
  • Knowledge, memory, planning – Maintain coherent behavior across long-running tasks.

Organizations can now sign up to deploy a single agent or launch full-scale agentic AI products. With this release, Autonomy positions itself as the all-in-one PaaS enabling enterprises to adopt agentic AI with reliability, trust, and unmatched scalability.

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