Vibe Coding is Easy.
Deploying AI Agents is Hard.

hirschgarten bridges that gap—turning your AI prototypes into production-ready agents with built-in observability, GitOps workflows, and native MCP integration. No more deployment headaches.

hirschgarten platform illustration
MCP Integration
Agent Workflow
Observability
GitOps Ready

From Prototype to Production

Deploy production-ready AI agents in seconds

<2s
Agent Deploy Time
100%
Observable
JSON
GitOps Workflows

Everything You Need for Production AI Agents

Built-in observability, visual workflows, and seamless deployment

Built-in Observability

Monitor and debug your agents in real-time with comprehensive tracing, logging, and performance metrics built into the platform.

Visual Workflow Editor

Design complex agent behaviors without boilerplate using our intuitive node-based editor.

Native MCP Integration

First-class support for Model Context Protocol, enabling seamless integration with AI tools and services.

Flexible Deployment

Run in our cloud or self-host on your own infrastructure with the same powerful developer experience.

GitOps Ready

Workflows stored as JSON files for version control, code review, and seamless CI/CD integration.

Monitoring Dashboard

Track performance, costs, and agent behavior at scale with comprehensive analytics and insights.

Visual Workflows with Built-in Observability

Design, deploy, and debug AI agents with comprehensive monitoring at every step

MCP
Protocol Support
Real-time
Observability
JSON
Workflow Files

AI-Powered Reasoning

Connect LLMs, tools, and data sources to create intelligent agents that reason and act autonomously.

Real-Time Observability

Watch every step of execution with live data flowing through each node and detailed performance traces.

MCP Protocol Support

Native Model Context Protocol integration for seamless AI tool connectivity and interoperability.

LLM Call
234ms
MCP Tool
45ms
Agent Action
12ms
Response
291ms total
Live Trace

Cost & Performance Analytics

Track token usage, API costs, and performance metrics across all your agents in real-time.

$0.023
Cost per run
291ms
Avg response
1.2k
Tokens used
99.9%
Success rate

Version Control Everything

Every workflow is stored as a JSON file. Commit to Git, review changes, roll back deployments, and maintain a complete audit trail.

+ "llm_call": { "model": "gpt-4-turbo", "temperature": 0.7 }
- "llm_call": { "model": "gpt-4", "temperature": 0.5 }
AI Agents Running

Ready to deploy production AI agents?

Join developers building reliable AI agents with h10n's end-to-end platform.