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 noticed only 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.”
SRE.ai is currently assembling an initial group of enterprise customers that will help test its platform before it becomes broadly available. The company will hire more engineers to support the development effort.
Photo: Unsplash
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