The Pulse
Resolve AI Raises $125M to Build Production-Engineering Agents
Resolve AI has raised $125 million in a Series A round led by Lightspeed Venture Partners, valuing the production-operations startup at $1 billion.
AI.info Team ·
“The next frontier for software engineering is applying AI to the problem of running software in production,” said Spiros Xanthos, Founder and CEO of Resolve AI. “AI has fundamentally changed how software is built; now it’s time to change how software runs. By applying AI to production operations, we’re accelerating the entire lifecycle of software and creating the foundation for a new era of innovation at scale.”
Spiros Xanthos, Founder and CEO, Resolve AI
Resolve AI announced on February 4, 2026, that it had raised $125 million in a non-blended Series A funding round at a $1 billion valuation. Lightspeed Venture Partners led the round. Existing investors Greylock Partners, which led the company’s seed round, Unusual Ventures, Artisanal Ventures and A* invested above their pro rata allocations.
The financing brings Resolve AI’s total funding to more than $150 million, 16 months after the company emerged from stealth. The company said it has won enterprise customers including Coinbase, DoorDash, MongoDB, MSCI, Salesforce and Zscaler.
Resolve AI Targets the Work After Code Is Written
Resolve AI is positioning its product around the work required to run software after it has been deployed. The company describes its product as “AI for prod,” a multi-agent system designed to operate across code, infrastructure and telemetry.
Its system is built to triage alerts, investigate and resolve incidents, surface production issues and provide engineers with production context as they write code. Resolve AI says each customer’s environment is unique, with the information needed to understand it distributed across running systems and changing continuously.
The company says its agents capture the tribal knowledge and distinctive behavior of each organization’s systems. They combine foundation and custom models with specialized agents trained to learn each organization’s technology stack, business logic and operational patterns.
“While software development has been one of the fastest-growing applications of AI, Spiros and Mayank recognized early that the real value, and the harder problem, is in production,” said Sebastian Duesterhoeft, Partner at Lightspeed Venture Partners. “They’re not just adding features; they’re building a full-stack AI company from the ground up with custom models and agents purpose-built for managing complex software in production. We believe Resolve AI is defining an entirely new category, and this will be one of the most important applications of AI in enterprise software.”
Sebastian Duesterhoeft, Partner, Lightspeed Venture Partners
Lightspeed Backs Production Operations
Resolve AI’s announcement frames software operations as a growing challenge for enterprises. Developers, site reliability engineers, platform engineers and support teams often manage separate portions of complex systems. Cloud infrastructure sprawl, frequent code changes and operational knowledge held in informal workflows can contribute to more incidents, slower recovery and increased operational work.
The company says the challenge is amplified by the amount of code generated by AI coding agents. As more software is produced, organizations need systems that can understand how their applications behave in production and help teams respond when failures occur.
Resolve AI was founded by Spiros Xanthos and Mayank Agarwal, whom the company describes as observability pioneers with more than 20 years of experience building and operating production systems at scale. The co-founders have two prior exits to Splunk and VMware, co-created OpenTelemetry and most recently led Splunk’s observability business.
The new funding will accelerate product development, expand Resolve AI’s engineering and go-to-market teams and support growing enterprise adoption. The company’s stated focus is to build production-specific agents and custom models that can help organizations run and maintain software in live environments.