Resolve AI announced it has raised $40 million in a Series A extension at a $1.5 billion valuation, alongside the launch of Resolve AI Labs, a new initiative focused on advancing AI systems for complex production environments. The round was led by DST Global and Salesforce Ventures, bringing Resolve AI’s total funding to more than $190 million just 18 months after emerging from stealth. The company serves enterprise customers, including Coinbase, DoorDash, MSCI, Salesforce, and Zscaler.
Resolve AI is focused on applying AI to operate and manage software in production, a domain that involves complex systems, fragmented telemetry, and high requirements for accuracy and reliability. The company’s platform combines custom AI models, production-specific agents, and systems expertise to help enterprises manage operational workflows more efficiently.
The newly launched Resolve AI Labs will concentrate on building domain-specific models and agentic systems tailored for production environments. The initiative will be led by Dhruv Mahajan, who joins as Chief AI Scientist after leading post-training efforts for large-scale foundation models at Meta.
Resolve AI Labs will focus on advancing several core areas, including model development and post-training for production operations, AI reasoning across telemetry such as logs and metrics, evaluation frameworks for reliability, synthetic data generation, and scalable system architectures. The effort also includes governance and guardrails to ensure safe and controlled AI deployment in production systems.
The company emphasizes that general-purpose AI models are not sufficient for production operations, where systems are constantly evolving and require precise, context-aware reasoning across multi-step workflows. Through close collaboration with enterprise partners, Resolve AI aims to develop models and agents capable of investigating incidents, diagnosing root causes, and taking action with varying levels of human oversight depending on risk.
Over time, the company envisions a transition from human-in-the-loop systems to increasingly autonomous operations, where AI agents handle the majority of production tasks while engineers focus on higher-level system design and innovation.
The new funding will support continued investment in Resolve AI’s platform, expansion of its go-to-market efforts, and long-term research through Resolve AI Labs, as the company works toward enabling AI-driven management of production environments at scale.
KEY QUOTES
“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. 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.”
Rahul Mehta, Co-Founder And Managing Partner, DST Global
“Foundation models are improving quickly, but they are still not enough for production operations. 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.”
Spiros Xanthos, Founder And CEO, Resolve AI
“As early investors in foundation models, we’ve seen firsthand how AI is reshaping how software gets built. 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.”
Zak Kokosa, Principal, Salesforce Ventures
“Running software at enterprise scale means production incidents can have significant costs in engineering time, customer trust, and business continuity. Resolve AI has changed how our teams work through them. 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.”
Meir Amiel, President, Chief Trust And Infrastructure Officer, Salesforce
“Production systems are noisy, incomplete, and constantly changing. 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.”
Dhruv Mahajan, Chief AI Scientist, Resolve AI
