Greylock-backed Resolve AI raises $35 million in seed funding to help engineers

Resolve AI, a startup aiming to automate software operations, has raised $35 million in seed funding from investors led by Greylock, as the latest entrants to the space of developing AI-powered tools for software engineers.

It is the largest check written so far this year by the Silicon Valley venture capital firm that has backed companies such as Airbnb and Meta. Stanford Professor Fei-Fei Li and Google DeepMind's Chief Scientist Jeff Dean also joined the round.

Founded earlier this year by Spiros Xanthos, a former Splunk executive, Resolve makes AI tools that can autonomously troubleshoot and fix production issues, reducing "Mean Time to Resolve" and allowing engineers to focus on development tasks.


While most AI engineer tools focus on code generation, Xanthos argues engineers spend much time on operational tasks like on-call duties, troubleshooting, and infrastructure management. These tasks require an understanding of code and specific production environments.

He said by building proprietary agentic systems, Resolve can autonomously handle alerts and incidents using tools such as AWS and GitHub, without human intervention in most cases.

"Our goal is to take over stressful and time consuming tasks, and offer the tool that could be much more intelligent and effective," said Xanthos.

The startup, self funded in the beginning, has already courted startup clients such as DataStax.

Xanthos said he plans to use the capital for hiring, aiming to double the current team of 16 people by year end.

The company is also looking to expand its AI tools to perform more tasks, such as incident prevention and cloud cost optimization.

"Reimagining software engineering with AI might be the biggest opportunity in generative AI," said Greylock partner Saam Motamedi, who led the investment.

"We look for companies where there's a very clear tie in to hard (return on investment). What Resolve is building is a very quantifiable space, and that's why they've been very quickly able to go out of this (proof of concept) stage into production relationships with customers."