Resolve AI Raises $40M Series A Extension at $1.5B Valuation

The company is valued at $1.5 billion. 18 months after emerging from stealth, Resolve AI has raised more than $190 million.

The company plans to use the funds to further develop its platform, expand its go-to-market efforts, and support long-term research.

The company also announced Resolve AI Labs, a new initiative focused on building specialized AI models and agent-based systems to manage complex production environments.

Resolve AI’s Resolve AI Labs will be led by Dhruv Mahajan, who joins as Chief AI Scientist. He previously worked at Meta, where he led post-training for large-scale Llama models. At Resolve AI, he will use this experience to build specialized AI models, testing systems, and agent-based tools for reliable use in real production environments.

General-purpose AI models are not designed for real production environments. In these settings, AI must handle noisy data, complex systems, and multi step workflows where errors can have serious consequences, while remaining highly accurate, fast, reliable and controllable.

Resolve AI Labs will focus on building the core AI systems needed to manage production environments. This includes developing domain-specific models and post-training methods that enable AI to reason across operational data such as logs, metrics, traces, and system events, and creating evaluation systems to measure accuracy and reliability in real workflows. It will also work on generating synthetic data, building simulation environments for training and testing, designing scalable system architectures, and adding governance and safety controls for AI operating in production.

Resolve AI Labs will work closely with large enterprises that run complex and critical production systems. These environments produce many signals, change constantly, and need highly accurate, domain-specific AI that standard models cannot provide. The company will use these real-world challenges to improve its models, training methods, and testing systems, enabling AI to work more effectively at scale.

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The goal is to create production systems where AI can help manage operations by investigating issues, finding root causes, and taking action. At the same time, humans stay involved based on risk and context.

"We're honored to partner with Spiros, Mayank, and the entire Resolve AI team to support their vision of bringing AI to production environments. With their extremely high talent density and decades of experience in the industry, this team is best positioned to win in leveraging AI to operate complex systems at scale," said Rahul Mehta, Co-founder and Managing Partner at DST Global. "What stood out to us about Resolve AI is their focus on the model, data, and systems work required to make AI truly effective in production."

"Foundation models are improving quickly, but they are still not enough for production operations," said Spiros Xanthos, Founder and CEO of Resolve AI. Production environments demand reasoning over fragmented telemetry, long-running workflows, constantly changing systems, and a very high bar for accuracy. We are forming the AI Labs because closing that gap requires domain specific models, post-training, and agentic systems designed specifically for this domain."

"As early investors in foundation models, we've seen firsthand how AI is reshaping how software gets built," said Zak Kokosa, Principal, Salesforce Ventures. "However, managing that software in complex production environments remains one of the hardest problems in enterprise engineering. It requires deep domain expertise layered on top of frontier AI, which is exactly what Resolve AI has pioneered. With a world-class team and proven traction among global enterprises, Resolve AI is uniquely positioned to lead the next phase of agentic AI operations. We are thrilled to partner with Spiros, Mayank, and the entire team."

"Production systems are noisy, incomplete, and constantly changing," said Dhruv Mahajan, Chief AI Scientist at Resolve AI. "Building AI that works in those environments requires advances in model building, reasoning, evaluation, and control systems. The opportunity is to take what foundation models make possible and turn it into systems that are actually accurate, reliable, and operationally useful in production."

"Running software at enterprise scale means production incidents can have high costs in engineering time, customer trust, and business continuity. Resolve AI has changed how our teams work through them," said Meir Amiel, President, Chief Trust and Infrastructure Officer, Salesforce. "What used to take hours of manual investigation and coordination across teams now gets resolved in a fraction of the time. Our engineers aren't only faster, they're focused on the work that actually drives impact."

About Resolve AI

Founded in 2024, by Spiros Xanthos and Mayank Agarwal, Resolve AI is an AI platform for running and managing software in production systems. Built by observability experts, it combines custom AI models, production-focused agents, and deep systems knowledge to solve complex software operation problems. Leading companies like Coinbase, DoorDash, MongoDB, MSCI, Salesforce and Zscaler use it to manage their production environments.

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