TITLE: Resolve AI valued at $1B in reported Series A funding round

Resolve AI Secures $1 Billion Valuation in Series A Funding

Resolve AI Inc., a startup specializing in AI-driven incident remediation for enterprise technology infrastructure, has reportedly raised Series A funding at a $1 billion valuation. The round, led by Lightspeed Venture Partners, features a multi-tranched structure where some shares were sold at valuations below $1 billion. Multiple investors participated, though specific names beyond the lead were not disclosed. The funding news, first reported on December 22, 2025, underscores growing investor interest in AI tools that automate complex IT troubleshooting.

The company previously secured $35 million in seed funding in 2024 from Greylock Partners, prominent AI researcher Fei-Fei Li and Google DeepMind Chief Scientist Jeff Dean. Resolve AI's founders, Spiros Xanthos and Mayank Agarwal, bring proven expertise; they sold their prior startup to Splunk Inc. in 2019.

Platform Capabilities and Technology

Resolve AI's core offering is an AI platform designed to help enterprises identify, diagnose and resolve technical issues in their infrastructure. The system ingests data from diverse sources, including cybersecurity tools, public cloud platforms, project management software like Jira and other enterprise systems. This raw data is transformed into a knowledge graph—a visual representation mapping infrastructure components and their interconnections.

Customers can customize the platform's data usage. For instance, engineers might direct the AI to focus solely on telemetry from a specific repository when investigating database outages. Upon detecting an issue, the platform generates multiple hypotheses for potential causes and deploys AI agents to test them concurrently. In a website outage scenario, one agent could probe for a distributed denial-of-service attack while another examines recent configuration changes.

During investigations, the system gathers supplementary data, such as reviewing support tickets to assess customer impact. Once analysis concludes, Resolve AI produces an incident timeline detailing the sequence of events and root cause. It also provides actionable remediation suggestions, including automated scripts—for example, a configuration revert for a faulty update.

Beyond remediation, the platform supports proactive tasks. Engineering teams can use it to identify performance optimization opportunities or reduce infrastructure costs. New administrators benefit from system familiarization features, accelerating onboarding in complex environments.

Market Context and Competitors

Resolve AI operates in a burgeoning sector where AI is automating manual IT operations, particularly incident management. The startup's funding arrives amid heightened demand for tools that minimize downtime in cloud-native and hybrid infrastructures. A competitor, Wild Moose Inc., recently raised $7 million from a group including Y Combinator, highlighting the competitive landscape for AI-driven troubleshooting solutions.

Enterprise adoption of such platforms is accelerating as organizations grapple with increasing complexity from AI integration, multi-cloud setups and cybersecurity threats. Resolve AI's approach emphasizes explainability and customization, differentiating it from more generalized AI ops tools. The company's valuation reflects confidence in its ability to scale amid these trends.

Broader Implications for AI in Enterprise IT

The funding round positions Resolve AI to expand its engineering team and enhance platform features, potentially integrating advanced AI models for predictive maintenance. As enterprises shift from reactive to proactive IT management, tools like Resolve AI could reduce mean time to resolution (MTTR) significantly, lowering operational costs and improving reliability.

Industry analysts note that AI remediation platforms address a critical pain point: the shortage of skilled DevOps engineers. By automating hypothesis testing and remediation, these systems enable smaller teams to handle larger-scale incidents. Resolve AI's knowledge graph, in particular, provides a unified view of sprawling infrastructures, which is invaluable for distributed teams.

Looking ahead, the startup faces challenges in data privacy and integration with legacy systems. However, its backing from luminaries like Li and Dean suggests strong technical foundations. As AI evolves, Resolve AI's focus on agentic workflows—where AI agents collaborate on tasks—aligns with emerging paradigms in autonomous operations.

This development occurs against a backdrop of robust venture activity in AI infrastructure. In 2025, investments in AI ops and security have surged, driven by regulatory pressures and the need for resilient digital ecosystems. Resolve AI's milestone validates the sector's potential, even as economic uncertainties persist.