Resolve AI Lands $125 Million Led by Lightspeed

<p><strong><span class&equals;"legendSpanClass">SAN FRANCISCO<&sol;span><&sol;strong> &&num;8212&semi; <u><a href&equals;"https&colon;&sol;&sol;edge&period;prnewswire&period;com&sol;c&sol;link&sol;&quest;t&equals;0&amp&semi;l&equals;en&amp&semi;o&equals;4610380-1&amp&semi;h&equals;3890495813&amp&semi;u&equals;https&percnt;3A&percnt;2F&percnt;2Fresolve&period;ai&percnt;2F&amp&semi;a&equals;Resolve&plus;AI" target&equals;"&lowbar;blank" rel&equals;"nofollow noopener">Resolve AI<&sol;a><&sol;u>&comma; a company developing AI for running and operating software in production&comma; has raised &dollar;125 million in a non-blended Series A funding at a &dollar;1 billion valuation&comma; led by Lightspeed Venture Partners&period; Existing investors Greylock Partners&comma; which led the company&&num;8217&semi;s seed round&comma; Unusual Ventures&comma; Artisanal Ventures&comma; and A&ast; invested above their pro rata in the round&period; Resolve AI has raised more than &dollar;150 million in total funding just 16 months after emerging from stealth&comma; rapidly winning enterprise customers including Coinbase&comma; DoorDash&comma; MongoDB&comma; MSCI&comma; Salesforce&comma; and Zscaler by helping engineering teams deliver more reliable customer experiences and move faster in production&comma; giving their businesses a sustained competitive edge&period;<&sol;p>&NewLine;<p>In modern enterprises&comma; how quickly software teams can ship code and operate production directly shapes their innovation velocity&period; Companies want their best engineers focused on building new features and improving customer experiences&period; Still&comma; in practice&comma; engineers spend most of their time in day-to-day operations and working on keeping software running in production&period; That work demands constant coordination across developers&comma; SREs&comma; platform engineers&comma; and support teams&comma; each responsible for only a portion of complex&comma; fast-changing systems&period; Cloud infrastructure sprawl&comma; frequent code changes&comma; and critical operational knowledge trapped in tribal workflows compound the challenge&comma; which is further amplified by the amount of code generated by AI coding agents&period; The result is more incidents&comma; slower recovery&comma; greater operational toil&comma; poor customer experience&comma; and increased risks&period;<&sol;p>&NewLine;<p>Resolve AI is pioneering the &&num;8220&semi;AI for prod&&num;8221&semi; category&colon; an AI system designed to run and maintain software in production&period; The company&&num;8217&semi;s multi-agent system operates across code&comma; infrastructure&comma; and telemetry to triage alerts&comma; autonomously investigate and resolve incidents&comma; proactively surface production issues&comma; and provide engineers with real production context as they write code&period; Each customer&&num;8217&semi;s environment is unique&comma; and the data needed to understand it exists only inside running systems and changes continuously&comma; placing it beyond the reach of general-purpose models&period; Resolve AI lives inside production&comma; capturing the tribal knowledge and unique behavior of each company&&num;8217&semi;s systems and uses it to reason and perform work across tool and team boundaries&period;<&sol;p>&NewLine;<p>&&num;8220&semi;The next frontier for software engineering is applying AI to the problem of running software in production&comma;&&num;8221&semi; said Spiros Xanthos&comma; Founder and CEO of Resolve AI&period; &&num;8220&semi;AI has fundamentally changed how software is built&semi; now it&&num;8217&semi;s time to change how software runs&period; By applying AI to production operations&comma; we&&num;8217&semi;re accelerating the entire lifecycle of software and creating the foundation for a new era of innovation at scale&period;&&num;8221&semi;<&sol;p>&NewLine;<p>The problem is uniquely difficult because the undocumented operational knowledge required to run these systems is impossible to codify or scale&period; Resolve AI solves this by combining foundation and custom models&comma; and training specialized agents that learn each organization&&num;8217&semi;s specific stack&comma; business logic&comma; and operational patterns&period;<&sol;p>&NewLine;<p>&&num;8220&semi;While software development has been one of the fastest-growing applications of AI&comma; Spiros and Mayank recognized early that the real value&comma; and the harder problem&comma; is in production&comma;&&num;8221&semi; said Sebastian Duesterhoeft&comma; Partner at Lightspeed Venture Partners&period; &&num;8220&semi;They&&num;8217&semi;re not just adding features&semi; they&&num;8217&semi;re building a full-stack AI company from the ground up with custom models and agents purpose-built for managing complex software in production&period; We believe Resolve AI is defining an entirely new category&comma; and this will be one of the most important applications of AI in enterprise software&period;&&num;8221&semi;<&sol;p>&NewLine;<p>Resolve AI was founded by Spiros Xanthos and Mayank Agarwal&comma; observability pioneers with more than 20 years of experience building and operating production systems at scale&period; The co-founders have two prior exits to Splunk and VMware&comma; co-created OpenTelemetry&comma; the global open-source standard for managing telemetry data&comma; and most recently led Splunk&&num;8217&semi;s observability business&period;<&sol;p>&NewLine;<p>The new funding will accelerate product development&comma; expand the engineering and go-to-market teams&comma; and support growing enterprise adoption as Resolve AI scales AI for prod&period;<&sol;p>&NewLine;

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