Cycles — Runtime authority for autonomous agents
Cycles is a self-hosted governance layer designed for developers who need to manage the operational risks of autonomous AI agents. Unlike standard monitoring tools that report errors after they occur, …
About Cycles — Runtime authority for autonomous agents
Cycles is a self-hosted governance layer designed for developers who need to manage the operational risks of autonomous AI agents. Unlike standard monitoring tools that report errors after they occur, …
Use Cases
Real-world scenarios where Cycles — Runtime authority for autonomous agents saves time.
Use Case 1: Preventing Runaway API Costs
Problem: Autonomous agents can enter recursive loops or retry storms, consuming thousands of dollars in LLM API credits in minutes.
Solution: Cycles acts as a pre-execution gatekeeper that reserves a specific budget before an action is allowed to proceed, terminating the process if limits are exceeded.
Example: A developer sets a $1.00 cap on a research agent task; if the agent attempts a loop that would cost $10.00, Cycles blocks the call before the provider is billed.
Use Case 2: Restricting High-Risk Actions
Problem: Agents with access to external tools might perform irreversible actions, such as deleting database records or sending unauthorized emails, due to prompt regressions.
Solution: The platform intercepts tool calls and enforces "blast radius" boundaries, allowing internal logic to proceed while blocking high-risk external mutations.
Example: A support agent is permitted to query a database but is blocked by Cycles when it attempts to send an automated email to 200 customers simultaneously.
Use Case 3: Multi-Tenant Resource Management
Problem: In SaaS applications, a single user's runaway agent can exhaust the entire platform's shared API quota, causing downtime for all other customers.
Solution: Developers use the governance layer to isolate budgets and permissions for every individual customer session.
Example: A platform provider ensures that Customer A's high-volume agent tasks never interfere with or consume the API capacity allocated to Customer B.
Key Features
What you get out of the box.
- Self-hosted pre-execution gatekeeper for autonomous agents
- Per-run and per-session budget enforcement caps
- Real-time interception of LLM and tool calls
- Multi-tenant isolation for shared API resources
- Signed audit logs for governance and compliance evidence
- Apache 2.0 licensed open-source architecture
- Native support for Python, TypeScript, and Java
- Integration with LangChain, OpenAI, Anthropic, and CrewAI
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