Optimize Performance, Cost, Speed & Carbon for each prompt
ModelPilot is an intelligent LLM router that automatically picks the best AI model for each prompt, balancing cost, latency, quality, and environmental impact. Unlike other tools, it’s a drop-in API replacement for OpenAI-style endpoints, meaning you can integrate it in minutes without changing your existing code.
Agentlify's smart routing automatically selects from 35+ models per step based on complexity and cost, with zero-latency static compilation at deploy time. Users pay provider costs at cost with no markup, plus $0.50/1M tokens routing fee. Custom Response Memories train routing on user data for best-in-class accuracy.
Agentlify works with LangChain, CrewAI, AutoGen, and Vercel AI SDK via OpenAI-compatible API. Users change only baseURL and apiKey, keeping existing code intact. Agents are called like models with model: 'agent:your-id', enabling drop-in integration.
Agentlify provides four composable optimizations: Adaptive Clarification (asks for missing info), Context Distillation (summarizes between steps), Constraint Verification (extracts and verifies requirements), and Dual Persona (skeptic critiques, resolver fixes). These run per-step with no hardcoded models, improving output quality and compliance.
Agentlify lets users create agents as composable workflows (research → plan → execute → review steps) that automatically route each step to the best model from 35+ options. Users deploy via OpenAI-compatible API with two lines of code change, enabling production-ready agents with streaming, tool calls, and built-in fallbacks.
Agentlify provides self-healing agents with automatic provider failover (e.g., OpenAI → Anthropic), error detection (4xx/5xx, timeouts, malformed responses), and model escalation (retry with stronger model). Agents stay alive in production loops with configurable fallback chains.