Lemony Launches cascadeflow: Cuts Costs By Up To 85% By Automatically Finding The Best and Least Expensive Language Model To Optimize Every Prompt, Agent Call and Query

NEW YORK, Nov. 6, 2025 /PRNewswire/ -- Lemony, an AI infrastructure company focused on business and developer innovation, today announced the launch of cascadeflow, a sophisticated tool that serves as a cascading system to intelligently and dynamically route AI queries to the best and least expensive language model available. Research indicates that 40-70% of text prompts and 20-60% of agent calls don't need expensive flagship models. Designed to dramatically reduce AI costs while maintaining quality and speed, cascadeflow helps enterprise and indie-developers launch and manage AI projects on budget.

"AI costs are spiraling, and most teams are still hardcoding large language models for every query," said Sascha Buehrle, Co-Founder and CEO, Lemony. "cascadeflow lets developers run smarter, not bigger, by dynamically choosing the right model for every task. It's a new standard for intelligent AI efficiency."

Unlike traditional model routers that rely on static rules, cascadeflow uses speculative execution with quality validation, accessing hundreds of specialists with one cascade. cascadeflow brings meaningful benefits, including that it:

• Speculatively executes small, fast models first - optimistic execution ($0.15-0.30/1M tokens)
• Validates quality of responses using configurable thresholds (completeness, confidence, correctness)
• Dynamically escalates to larger models only when quality validation fails ($1.25-3.00/1M tokens)
• Learns patterns to optimize future cascading decisions and domain specific routing

With support for OpenAI, Anthropic, Groq, vLLM, Ollama, and more, cascadeflow works seamlessly across multiple providers, offering developers flexibility and performance without vendor lock-in. It's fully open source under the MIT license, offering type safety, async architecture, and built-in monitoring. Developers will use cascadeflow for:

• Cost Optimization. Reduce API costs by 40-85% through intelligent model cascading and speculative execution with automatic per-query cost tracking.
• Cost Control and Transparency. Built-in telemetry for query, model, and provider-level cost tracking with configurable budget limits and programmable spending caps.
• Speed Optimization. Cascade simple queries to fast models (sub-50ms) while reserving expensive models for complex reasoning, achieving 2-10x latency reduction.
• Multi-Provider Flexibility. Unified API across OpenAI, Anthropic, Groq, Ollama, vLLM, Together, and Hugging Face with automatic provider detection and zero vendor lock-in.
• Edge & Local-Hosted AI Deployment. Use best of both worlds: handle most queries with local models (vLLM, Ollama), then automatically escalate complex queries to cloud providers only when needed.

"Our mission is to democratize efficient AI," said Buehrle. "With cascadeflow, developers can plug in any model provider and immediately start saving, all while maintaining performance and reliability."

cascadeflow is available today on GitHub at https://github.com/lemony-ai/cascadeflow and as an n8n integration (n8n community nodes n8n-nodes-cascadeflow).

About Lemony
Lemony builds open, developer-focused AI infrastructure tools that make machine learning more efficient, transparent, and cost-effective. The company's mission is to help developers harness powerful AI while keeping costs predictable and accessible while preparing for a future where hundreds of domain-specific small language models need to work safely together.

SOURCE Lemony