We have plenty of AI Agents. What we lack is a Manager.
The Enterprise AI landscape is fragmented. You have a customer service agent built on an external platform. A data analysis agent coded in Python by your internal team. GTM agents outsourced from a startup. Individually, they are powerful. Together, they are a mess.
Currently, companies try to glue these disparate agents together with complex, brittle automation scripts. This creates a high barrier to entry: only engineers can build the flows, and only engineers can fix them when they inevitably break.
This is the "Integration Wall." And it is killing productivity.
At Mindra, we believe the solution is Dynamic Orchestration.
Imagine a non-technical employee simply chatting with a central interface—like they do with ChatGPT. They assign a complex, multi-stage objective.
Behind the scenes, Mindra’s Orchestrator Agent: Deconstructs the prompt. Assigns tasks to the best-fit agent (regardless of its language or origin). Validates the results.
We are moving away from "workflow maintenance" to true "outcome management."
Your agents don't need to be recoded. They just need to be led.
Stay Updated
Get the latest articles on AI orchestration, multi-agent systems, and automation delivered to your inbox.

Written by
Zeynep Yorulmaz
Co-Founder & CEO at Mindra. Building the future of AI agent orchestration.
Related Articles
Universal Agent Connectivity: The Complete Guide to Unified AI Infrastructure in 2026
Organizations accumulate diverse AI capabilities from multiple vendors, frameworks, and internal development efforts..
AI Agent Orchestration: The Complete Enterprise Guide for 2026
AI agent orchestration has emerged as the critical infrastructure that enables enterprises to harness the full potential of their AI investments.
Will AI agents share the fate of mobile apps?
When apps first came to App Store, there were a lot of independent developers that benefited from the empty market, specific apps for specific situations could sell very good.