Build, Run, and Scale Agents with one SDK.
The fastest way to ship production AI agents. Call agents like models — steps, skills, and streaming built in. Change 2 lines of code.
npm install agentlify
Everything you need
to ship agents fast
One SDK. One endpoint. Production-ready agents with streaming, tool calls, fallbacks, and observability — all built in.
Instant API
Turn any agent workflow into a production API endpoint with built-in auth and monitoring.
Orchestration
Chain complex steps: Research → Plan → Execute → Review. Handle dependencies effortlessly.
Live Streaming
Stream your agent's thought process, tool calls, and outputs in real-time to your UI.
Agent Templates
Start with battle-tested patterns for Coding, Research, or Support agents. Fork and customize.
Intelligent Optimizations
Four composable layers to ground your agents, reduce hallucinations, and ensure compliance — without changing your prompt.
Clarification Gate
Pauses execution to ask the user clarifying questions when input is ambiguous. Prevents wasted runs.
Context Distillation
Summarizes facts, decisions, and constraints between steps. Keeps multi-step agents focused as context grows.
Constraint Guard
Extracts requirements from user input and verifies every step adheres to them before proceeding.
Dual Persona
A "Skeptic" model critiques the output, and a "Resolver" model fixes flaws. Reduces hallucinations.
Up and running
in 3 steps
Drop in your existing code. Point to the Agentlify endpoint. Your agent is now production-ready.
Configure Brain
Set up your agent's core optimization: prioritize intelligence for planning, or speed for chat.
Connect Tools
Drop in your existing LangChain, CrewAI, or AutoGen code. Point to the Agentlify endpoint.
Run & Optimize
Your agent now automatically handles model fallbacks, rate limits, and selects the best model for each step.
Compatible with your Framework
Whether you use LangChain, CrewAI, or raw OpenAI SDKs, Agentlify seamlessly integrates to make your agents more reliable and cost-effective.
import OpenAI from "openai"
const client = new OpenAI({
apiKey: process.env.OPENAI_API_KEY,
baseURL: "https://api.openai.com/v1"
})import OpenAI from "openai"
const client = new OpenAI({
apiKey: process.env.AGENTLIFY_API_KEY,
baseURL: "https://agentlify.co/api/v1/agent/{agentId}"
})Pick your
optimization profile
Different agents need different brains. Configure the perfect balance of intelligence, speed, and cost for each use case.
Expert & Coder
Max intelligence
Best for: Coding agents, complex planning, research, and analysis
Assistant
Balanced profile
Best for: Customer support, general chatbots, interactive agents
Worker
Max throughput
Best for: Data extraction, classification, summarization tasks
Self-healing &
Reliable
Agents crash when models fail. Agentlify prevents this by automatically handling errors, retrying with fallbacks, and keeping your agent loop alive.
Provider failover
If OpenAI is down, route to Anthropic. If rate limited, try another provider. Configurable fallback chains.
Error detection
Detects 4xx/5xx errors, timeouts, malformed responses, and rate limits. Triggers automatic retry logic.
Model escalation
If a cheap model fails, retry with a stronger one. GPT-5-mini fails? Try Claude Sonnet. Still failing? GPT-5.
Handles edge cases
Rate limits
Timeouts
Provider outages
Malformed JSON
Context-aware
learning
Agents get smarter over time. Analyze past interactions to train custom brains that select the perfect model for your agent's specific domain and tools.
Compiled
instructions
Runtime optimizers add 2-3 seconds of latency per step. Agentlify compiles your agent instructions and prompts statically—zero added latency at runtime.
Zero-latency execution
Optimizations are applied to your templates at deploy time. No intermediate LLM calls in the hot path.
Model-specific formatting
Automatically formats prompts for the target model (e.g., XML tags for Claude, structured markers for GPT-4).
Static few-shot injection
We analyze your historical logs to find the best few-shot examples and bake them into your prompt templates.
Requires LLM roundtrip to rewrite prompt
Pre-computed at deploy time
Use XML tags for clear separation...
</claude_formatting>
Debate Mode
3 models, 1 best answer
For high-stakes decisions where accuracy is everything. Debate mode sends your request to 3 models from different families in parallel, then an arbitrator synthesizes the best possible answer.
Diverse perspectives
Panelists are automatically selected from distinct model families — GPT, Claude, Gemini — ensuring genuinely different reasoning approaches.
Intelligent arbitration
A top-tier model evaluates all responses and produces a single, synthesized answer that combines the best insights.
Multiple activation methods
Enable globally on your router, per-request via the API, or use the /debate preset.
const response = await agentlify.chat({
model: "router/my-router",
messages: [{
role: "user",
content: "Analyze the trade-offs..."
}],
debate: true // 3 models + arbitrator
});Carbon tracking
per request
Every API response includes estimated CO₂e based on model size, architecture (dense vs MoE), and provider region. Export reports for ESG compliance.
CO₂e estimates in response headers and dashboard analytics
Optionally weight routing decisions by environmental impact
Export monthly carbon reports for compliance documentation
Deploy your agent
in 2 minutes
Create an agent, drop in your logic, done. Free tier includes $5 in credits. No credit card required.
npm install agentlify • OpenAI SDK compatible