Autoheal Raised $7.9 Million for Enterprise AI Agents
The startup built an orchestration platform to manage and improve automated software development agents.
Updated on Sept. 28, 2026 in Artificial Intelligence
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Autoheal secured $7.9 million in a seed funding round led by Innovation Endeavors to scale its infrastructure for managing enterprise AI agents. The platform is currently used by companies including Nomura Bank, AvidXchange, and Empiric Earth to integrate coding agents with development workflows.
Why it matters
Repetitive software development lifecycle tasks consume more than one-third of engineering capacity, creating a need for unified systems to manage AI autonomy. Autoheal seeks to address this by providing a centralized model to scale these agents securely.
The platform connects disparate coding agents, repositories, and cloud runtimes into a shared context graph. It uses an Evaluator agent to score performance based on review comments and CI failures, while a Healer agent automates fixes by submitting pull requests.
The players
Autoheal
An enterprise infrastructure startup that provides orchestration for autonomous AI coding agents and development workflows.
Innovation Endeavors
A venture capital firm focused on deep technology investments that led the seed round.
The details
Autoheal functions by integrating directly with git-based version control systems to track all behavior changes, requiring human engineer approval for modifications. The system acts as an orchestration layer for enterprise AI, leveraging infrastructure to audit and iterate on the performance of autonomous worker agents. All development actions occur within security boundaries to maintain compliance.
Timeline
September 28, 2026: Announcement of the $7.9 million seed funding round.
The Tech Race
This development follows a trajectory established by the founders' success in scaling the Harness platform to $200 million in ARR. Autoheal is positioning itself at the center of a shift toward managing autonomous enterprise agents rather than just static CI/CD pipelines.
Engineering teams at enterprises can currently utilize the platform to bridge existing coding agents with their internal observability tools and issue trackers. Users should note that all autonomous behavior changes require human engineer approval through git-based workflows.
The takeaway
The company aims to transition from general orchestration toward training private, enterprise-specific small language models using reinforcement learning on internal engineering data. Watch for the company's progress in developing sovereign intelligence models as a key indicator of its long-term growth.
Further reading
For broader context on how enterprise software is changing, see the latest updates in /tech/artificial-intelligence/.
More information
Learn more about the infrastructure platform on the Autoheal company website.
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Do you trust AI agents to manage and fix critical software engineering incidents?
