Developer Platform for AI Agents

You write the agent.
We handle the
streaming.

The gap between an agent script and a production agent system is enormous. Reminix closes it with one line of code.

support_bot.pyyour code
from langchain import create_agent
from reminix_runtime import serve, memory, kb
 
agent = create_agent(
model="gpt-4o",
tools=[memory, kb, my_tools]
)
 
serve(agent)
terminalwhat you get
$ reminix agent invoke support-bot \
--prompt "How do I reset my password?"
 
✓ Agent responded (142 tokens)
tools: knowledge_base
 
Go to Settings → Security → Reset Password.
You'll receive a confirmation email within
a few minutes.

Ship agents, not infrastructure.

Deploying an agent on a generic PaaS means building all of this yourself. Reminix gives it to you out of the box.

Streaming infrastructure

SSE endpoints, backpressure handling, client reconnection. Built in.

Conversation state

Multi-turn sessions, message history, user-scoped persistence. Managed for you.

Tool orchestration

Your agent calls tools, we execute them, handle timeouts, and return results.

REST APIs & SDKs

Production endpoints + typed Python and TypeScript clients. Works with every agent.

Auth & secrets

API keys, environment variables, rate limiting. No DIY auth middleware.

Monitoring & logs

Request tracing, error tracking, latency metrics. Not another Datadog config.

Tools that would take weeks to build.

Managed services your agent can call with zero setup. Add them with a single string — no infra to provision.

Memory

"memory"

User-scoped persistent memory across conversations. No vector DB pipeline to build.

Knowledge Base

"knowledge_base"

Upload docs, we handle chunking, embedding, and retrieval. Project-scoped RAG out of the box.

Web Search

"web_search"

Search the web and fetch page content. No API keys to rotate, no rate limits to handle.

KV Storage

"kv_storage"

Persistent key-value store for state, caches, and structured data. No database to provision.

Plus deploy your own tools in Python or TypeScript. Mix built-in and custom tools freely.

See how tools work

One line to production.

Wrap your existing agent with serve(). We handle everything else.

1

Write your agent

Use LangChain, Vercel AI, OpenAI, Anthropic, or the Reminix Runtime. Any framework, any model. Your code, your way.

2

Add serve(agent)

One line gives you production APIs, streaming, built-in tools, SDKs, and monitoring. No HTTP layer to write, no infra to configure.

3

Deploy

reminix deploy and you're live. Scaling, secrets, versions, rollbacks — all handled.

terminal

Deploy via reminix deploy or connect your GitHub repo for automatic deploys on every push.

Three patterns. Pick yours.

Each optimized for different problems. The platform handles tools, streaming, state, and infrastructure either way.

Chat

Multi-turn conversations with managed state and memory. Support bots, assistants, research agents.

Task

Stateless single-shot execution. Data processing, extraction, reports, code analysis.

Workflow

Multi-step orchestration with branching, approvals, and parallel execution.

See code examples for each pattern

Deploy your first agent in five minutes.

Free tier included. No credit card required.