System status: ready.sys

Turn prompts into pipelines

The open-source orchestration layer for LLM workflows. Build agents from the ground up. Run where data lives.

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Why AgentFlow?

Most agent platforms lock you in and send your data to external servers. AgentFlow is built for complete control, absolute security, and zero vendor lock-in.

[AF-01]

Security-First

Run where your data lives. Your pipeline runs inside your secure cloud or on-premise infrastructure. No leakage, no external processing.

[AF-02]

No Vendor Lock

Our stack is completely open-source. Build pipelines that belong to you, without recurring fees or dependencies on proprietary platforms.

[AF-03]

Your Stack

Bring your own infrastructure, custom tools, and models. Connect local LLMs, commercial APIs, or open models without friction.

How It Works

Go from raw prompts to robust autonomous LLM workflows in three simple steps.

01

Connect

Link your local models, vector stores, API keys, and custom developer tools.

02

Configure

Define routing rules, agent profiles, session states, and tool bindings in clean YAML.

03

Deploy

Spin up your agent workspace, connect it to your app, or run it headless as a CLI daemon.

Architecture Specification v2.0 // Local Security Boundary Online
LOCAL SECURITY BOUNDARY Developer Client CLI / WEB UI Agent Daemon local runtime Model Router MCP support Vector Cache sqlite / local-first LLM Provider openrouter / api Frontend Backend Database External

Core Capabilities

AgentFlow comes pre-loaded with powerful tools, memory modules, and multi-agent routing engines.

[FE-01]

Multi-Provider Routing

Seamlessly route tasks to OpenRouter, Gemini, Codex, or local instances via LM Studio. Choose cost, speed, or intelligence dynamically.

OpenRouter Gemini LM Studio
[FE-02]

Specialized Agent Profiles

Load pre-configured profiles like TARS, research assistants, or coder agents. Define personality, temperature, system constraints in YAML.

TARS Researchers Coders
[FE-03]

Protocol Tool Integrations

Equipped with full Model Context Protocol (MCP) support. Bind external databases, code runtimes, or custom files as execution tools.

MCP Spec Local Filesystem
[FE-04]

Skills & Semantic Memory

Session-aware vector caches preserve long-term context and let agents learn skills dynamically. Maintain context across multiple conversation boundaries.

Vector Cache SQLite Store
[FE-05]

Telegram Bot Integration

Run your workflows directly from Telegram. Chat with agents, trigger scheduled execution flows, and receive notifications via inline commands.

Telegram API Cron Engine
[FE-06]

Local-First Isolation

Keep code execution, configuration registries, and state storage completely local. Perfect for offline tasks and sensitive data projects.

Local Disk 100% Offline

Flexible Pricing Plan

Scale your agent operations with transparent, affordable plans. All options include the open-source CLI engine.

Free

$0
Forever
  • Basic MD prompt builder
  • Git workflow sync
  • GitHub open-source stack
  • Local-only configuration
Get Started
Sweet Spot

Premium

$9.99
Per Month
  • Multi-AI model routing
  • Cloud storage & sync
  • Saved template library
  • Structured JSON outputs
  • Advanced skills support
Upgrade to Premium

Pro

$19.99
Per Month
  • Preloaded orchestration runtimes
  • Priority support channels
  • Custom skills authoring
  • Team-wide workspaces
Go Pro

Looking for private deployments, custom tool integrations, team training, or SLA guarantees? We shape AI to work for you. You use the free tier. We handle the hard parts. You keep the keys.

  • Custom agent workflows
  • On-premise deployment
  • Engineering training
  • Enterprise SLAs
[Secure Portal]