cascadeflow Information

cascadeflow is the agent runtime intelligence layer. We sit inside AI agent execution and optimize every decision — model calls, tool calls, sub-agent handoffs — across cost, latency, quality, compliance, and energy. Not a router. Not a proxy. A governance system inside the loop. How it works: cascadeflow starts with efficient models, validates quality during generation, and escalates only when needed. Four enforcement actions — allow, switch_model, deny_tool, stop — give you direct control over agent behavior at runtime. Sub-5ms overhead. Results: 69% savings (MT-Bench), 93% (GSM8K), 52% (MMLU), 80% (TruthfulQA) — retaining 96% GPT-4 quality. Works with your stack: LangChain, LangGraph, Vercel AI SDK, Google ADK, OpenAI Agents SDK, CrewAI, n8n. Supports OpenAI, Anthropic, Groq, Ollama, vLLM, Together AI, HuggingFace + 100 more via LiteLLM. 3 lines of code: pip install cascadeflow / npm install @cascadeflow/core Open source (MIT). 286 GitHub stars. 17K+ downloads. 94 forks. cascadeflow Studio: closed beta for enterprise teams needing budget enforcement, compliance gates, KPI weights, and audit trails. Built by Lemony Inc. (NYC / Switzerland). github.com/lemony-ai/cascadeflow cascadeflow.ai