SRE.ai Launches with $7.2M Seed Funding to Revolutionize DevOps with AI-Powered Automation

Y Combinator alum SRE.ai raises $7.2M for DevOps AI agents | TechCrunch

"It wasn't one big lightbulb; it was death by a thousand cuts," Edward Aryee said when asked what led him and his co-founder, Raj Kadiyala, to launch SRE.ai. The company is offering natural language AI agents that can perform complex enterprise DevOps workflows like continuous integration and testing. "Instead of stitching together different low-code tools for enterprise applications like Salesforce, compared to products built on AWS, GCP, or Azure, teams can now move faster with context-driven, chat-like experiences that work across all of them," Kadiyala, who is the company's CEO, told TechCrunch. The duo thought of the product while working at Google Research and DeepMind. Aryee, SRE.ai's CTO, said they noticed the divide between the infrastructure tooling they had access to versus what others who didn't work at Google had to use. Their engineer friends lamented about tedious tasks, like untangling metadata conflicts. "It gnawed at us," Aryee said. He and Kadiyala realized: "The next generation of DevOps experiences needed to be created." So they founded SRE.ai in 2024 to offer more modern tools to enterprises so they can avoid issues like metadata merge conflicts. Other competing players include Copado, Gersetm, and Flosum. But Kadiyala said SRE.ai is different in that it works across multiple platforms spanning from AWS to ServiceNow. The company officially came out of stealth on Wednesday and announced a $7.2 million seed round led by Salesforce Ventures and Crane Venture Partners. Aryee said the SRE.ai onboarding process involves a setup where SRE.ai tools automatically connect with the user's integrations. The tool can then be customized for a user's needs like release pipelines, insight dashboards, and data monitoring. Meanwhile, SRE.ai has agents monitoring in the background to flag issues that need attention, such as security risks. The tool then offers recommendations on how to solve the problems. This leaves human IT teams free to tackle bigger, more meaningful projects, rather than being focused on tiresome tasks. Kadiyala described the fundraising process as "high conviction," and noted the round was oversubscribed. The company partook in YC's Fall '24 cohort, which helped Ayree and Kadiyala meet their lead investors. They will use the fresh capital to hire AI engineers and Salesforce experts. "We're seeing a lot of early traction, we're excited about building out our team to support new customers and extend the platform with new features," he said.

DevOps automation startup SRE.ai launches with $7.2M in funding - SiliconANGLE

SRE.ai Inc., a startup using artificial intelligence to make software teams more productive, launched today with $7.2 million in initial funding. Salesforce Ventures and Crane Venture Partners jointly led the seed investment. Releasing software to production involves multiple steps. Developers first scan the new code for security vulnerabilities and other flaws. After the code is turned into a functioning application, it's tested in a cloud-based sandbox. In some cases, the application's launch is also preceded by another test called a canary release. San Francisco-based SRE.ai offers a cloud platform that uses AI to automate software rollouts. The company was founded last year by Chief Executive Officer Raj Kadiyala and Chief Technology Officer Edward Aryee. The duo previously held engineering roles at Alphabet Inc.'s Google DeepMind lab. Before releasing a piece of code to production, engineers can ask a chatbot built into SRE.ai to check for bugs. The platform searches for issues by analyzing data in the applications that a software team uses to manage its work. After identifying a bug, SRE.ai can explain it and identify similar flaws that emerged in the past. The platform is capable of fixing some issues automatically. If a cloud environment that developers use to test new software exceeds its infrastructure usage limits, the platform can temporarily increase those limits. According to SRE.ai, developers can also use its platform to create new test environments from scratch. The software provisions infrastructure and installs any sample datasets that may be necessary for software evaluations. Users can optionally configure the sandbox to shut down automatically once testing is complete. In some cases, software flaws are only noticed after an application is deployed to production. SRE.ai includes a rollback tool that enables developers to quickly revert faulty updates. Software teams can also instruct the built-in chatbot to release new code to only a limited number of production users at first, which helps limit the impact of bugs. SRE.ai can perform actions in response to not only user prompts but also project milestones. For example, the platform could be configured to automatically spin up a testing environment whenever a developer makes changes to an application's code base. "DevOps in today's enterprise is more than just supporting traditional software development - it's the critical requirement for every class of business application," Kadiyala said. "Many mission critical business applications today were never designed for the scale, complexity, or speed of AI. We're fixing that."