cascadeflow Studio is an open-source runtime governance layer designed to operate within AI agents, providing oversight and control at every step of agent execution. The platform observes, scores, and enforces policies on each model call, tool call, and handoff, enabling users to align agent behavior with business goals and compliance requirements. Its in-process architecture allows cascadeflow to steer decisions in real time, applying user-defined policies and KPIs such as cost, latency, quality, budget, compliance, and energy, as well as custom dimensions defined in its Studio Policy Builder.
The tool supports a wide range of agent frameworks, including LangChain, OpenAI Agents SDK, CrewAI, PydanticAI, Google ADK, Vercel AI, n8n, OpenClaw, and Hermes Agent. It integrates with numerous model and tool providers, such as OpenAI, Anthropic, Groq, Together, on-prem vLLM, Ollama, and more than 17 others. cascadeflow offers eight runtime enforcement actions, including allowing or denying steps, switching models mid-run, blocking tool calls, terminating execution, retrying, requiring approval, redacting, and serving from cache. The Studio Domain Builder enables users to visually map domains to specialized model cascades and configure domain-aware routing, optimizing performance and cost by leveraging domain-specific models.
cascadeflow Studio provides business intelligence features such as real-time cost breakdowns, spending forecasts, exportable reports, and fleet-wide KPI enforcement. Its audit trail and analytics capabilities support compliance and transparency, while role-based access, SSO/SAML, audit logs, and multi-organization workspaces address enterprise governance needs. The platform is framework-neutral, easy to integrate, and introduces less than 5 milliseconds of overhead per step. It is distributed under the MIT open-source license and can be installed via pip or npm. Integrations with Slack, Datadog, and finance stacks are also available, and the system continuously learns from agent runs to improve routing and optimization over time.
cascadeflow Studio is an Other AI product. It focuses on reducing AI inference costs and improving control over agent model selection and execution. cascadeflow Studio is an open-source project aimed at AI developers and engineers building agentic workflows. The project is open source (MIT). cascadeflow Studio is available on the web and the command line, and it can be self-hosted.
It is developed by lemony-ai, and the product first shipped in 2025. The project is developed in the open on GitHub with 3.2k stars and 9 commits in the last 90 days. Among its 7 catalogued features are model cascading, cost optimization, and audit trail. It exposes integrations via a public API.
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