You can start by requesting a demo. Our team will walk you through the platform, help with integrations, and guide you based on your specific use case — whether it’s LLMOps, RAG workflows, or GenAI application deployment.

FloTorch enables cost optimization through intelligent caching, LLM routing based on latency/cost thresholds, and usage analytics. You can monitor token consumption, detect inefficiencies, and automatically route queries to the most cost-effective models.

Yes. FloTorch is designed to be model-agnostic and framework-flexible. You can plug in any proprietary or open-source LLM, use agent frameworks like LangChain or CrewAI, and customize execution flows through no-code and API interfaces.