Requesty
AI Agent Infrastructure

Infrastructure for
AI agents

Your agents need reliable multi-model access, automatic failover, and cost controls. Requesty handles the infrastructure so you can focus on agent logic.

langchain_agent.py

from langchain_openai import ChatOpenAI

llm = ChatOpenAI(

base_url="https://router.requesty.ai/v1",

api_key="rq-...",

model="anthropic/claude-sonnet-4-20250514",

)

# Failover, caching, and routing handled

# automatically for every agent call.

crewai_agent.py

import os

os.environ["OPENAI_BASE_URL"] = \

"https://router.requesty.ai/v1"

os.environ["OPENAI_API_KEY"] = \

"rq-..."

# CrewAI, AutoGen, or any

# OpenAI-compatible framework

# Budget guardrails prevent runaway costs.

400+
Models available
99.99%
Uptime SLA
60%
Cost savings
10$
Free credits
Trusted by teams at
Shopify
Amadeus
Chargebee
Contentful
Demandbase
Pfizer
PWC
Capgemini
Sage
Siemens
Relevance AI
Appnovation
Shopify
Amadeus
Chargebee
Contentful
Demandbase
Pfizer
PWC
Capgemini
Sage
Siemens
Relevance AI
Appnovation

What agents need

Reliable, cost-effective multi-model access with automatic failover and budget guardrails.

Reliability

Agents cannot stop mid-task. Automatic failover across providers means your agent never hits a dead end.

Multi-model access

Use fast models for classification, smart models for reasoning. Route dynamically per-task through one API.

Cost control

Set budgets per agent, per user. Prevent runaway costs from infinite loops. Kill switch for rogue agents.

Caching

Tool calls repeat. Cache saves 40-60% on common agent patterns. Same results, fraction of the cost.

Request tracing

See every step your agent took. Token usage, model selection, latency per step. Debug production agents.

Rate limit handling

Agents send bursts. Requesty queues and retries automatically. No 429s interrupting multi-step workflows.

Works with your framework

Any framework that speaks the OpenAI format works with Requesty. Just change the base URL.

LangChain
CrewAI
AutoGen
Vercel AI SDK
LlamaIndex
Claude Code
Cursor
Aider
Continue
Custom Python
Custom TypeScript

Agent-specific features

Per-request model selection

Fast models for simple tasks, powerful models for complex reasoning. Route dynamically based on the step.

Budget guardrails

Set hard spending limits per agent or per user. Automatic cutoff prevents infinite loops from draining credits.

Request tracing

Full trace of every step: which model, how many tokens, what latency, what cost. Debug agents in production.

MCP server support

Connect your agents to external tools and data sources through the Model Context Protocol.

$10 free credits. Build agents that do not break.

No credit card required. Works with every major agent framework.