Today, we're introducing AgentDock to solve the operational complexity that kills AI automation projects-from sophisticated agents to reliable internal apps that augment your team's output.
The Hidden Crisis in AI Development
Every engineering team building with AI hits the same wall. It's not the models that break-it's the operational nightmare that comes after the demo.
Here's what actually happens when you try to build production AI agents:
- Day 1: You prototype with OpenAI. It works beautifully.
- Week 1: You add Anthropic for reliability. Now you're managing two APIs.
- Week 2: You need voice synthesis, communication APIs, data enrichment services.
- Month 1: You're juggling relationships with multiple service providers, each with unique rate limits, billing cycles, and failure modes.
- Month 3: Your "simple" AI agent requires significant operational overhead just to keep running.
This pattern repeats everywhere: death by a thousand API keys.
The Real Problem: Operational Friction Kills Innovation
The fundamental challenge in building AI agents isn't technical complexity - it's operational overhead.
AgentDock: Two Powerful Solutions
We built AgentDock to solve this systematically. Our approach starts with open-source foundations and scales to unified service access:
1. AgentDock Core (Open Source)
Our MIT-licensed runtime provides the foundational framework for building AI agents and automation.
2. AgentDock Pro (Unified Platform)
One API key. Every service. Zero operational overhead.