Autoheal, a company building a self-improving software factory for enterprise engineering teams, has raised US$7.9 million in Seed funding. The round was led by Innovation Endeavors, with participation from a group of venture and angel investors. The investment will support Autoheal's mission to help enterprises build, deploy, govern, and continuously improve multiplayer cloud AI agents across the software development lifecycle.
The Need for a New Operating Model
AI coding tools are increasing engineering velocity but also adding operational burdens such as incident response, security remediation, and token cost control. Platform engineering teams are shifting toward a software factory model powered by specialized AI agents. However, fragmented tools, limited shared context, and strict security constraints often prevent these agents from scaling reliably.
Inside the Software Factory
Autoheal connects existing coding agents, code repositories, CI/CD pipelines, observability systems, cloud runtimes, and issue trackers into a shared engineering context graph. This gives every worker agent access to the same engineering context, secure production access, private evaluation infrastructure, and cost controls. The platform also integrates with existing coding agents rather than replacing them.
A Continuous Healing Loop
As worker agents execute repetitive post-coding workflows, two self-improvement agents operate continuously in the background. The Evaluator agent assesses agent performance, while the Healer agent applies improvements based on those evaluations. This continuous loop helps platform teams reduce manual oversight, improve agent accuracy, and keep agents aligned with changing organizational knowledge.
Proven Results in Regulated Environments
Autoheal is already deployed in complex regulated environments, including Nomura Bank, AvidXchange, and Empiric Earth. Sameer Jain, CIO for Wholesale at Nomura Bank, said the platform reduces investigation timelines from hours to minutes while running entirely inside the bank's own cloud. Krish Shetty, CTO and SVP at AvidXchange, said Autoheal cut time to root cause to minutes and delivered evidence engineers trust.
Funding and Investor Support
Alongside Innovation Endeavors, the Seed round included backing from Emergent Ventures, U&I Ventures, Darkmode Ventures, Batch Ventures, and Param Hansa Values. Angel investors included Shawn Kung, Founder of GIT100; Sumeet Arora, Chief Product Officer of Teradata; Anshu Sharma, Co-Founder and CEO of Skyflow; Savin Goyal, Co-Founder and CTO of Outerbounds; and Srikant Gokulnatha, former SVP at ThoughtSpot. Harpinder Singh of Innovation Endeavors will join Autoheal's board.
Founding Experience and Vision
Autoheal grew out of the founders' experience building enterprise engineering and AI platforms at Harness, Microsoft Azure, ThoughtSpot, and AppDynamics. After scaling Harness to over US$200 million in annual recurring revenue, the team recognized that safely deploying AI agents across the SDLC had become time and token consuming. Harpinder Singh of Innovation Endeavors noted that enterprises are moving from experimenting with AI agents to operating them safely and efficiently at scale.
Future Roadmap
Autoheal plans to capture private engineering data by operating the factory and then train small customer-specific models that are sovereign and cost effective. Frontier models are trained on public internet data, open source code, and synthetic data, but enterprises want intelligence built on their own private data. The company also sees the same architecture extending beyond software engineering into data and security engineering.
Autoheal is positioning itself as the control plane for a new generation of enterprise AI agents that handle incident response, security remediation, and cost management. With fresh Seed funding and early traction in regulated industries, the company is addressing a growing operational gap in software development. Its self-improving approach could become a foundational layer for how large enterprises govern and scale AI across the software lifecycle.