Resolve AI

AI SRE that goes on call for engineering teams and investigates production issues.

Custom quoteAI site reliability engineering (SRE) agent

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Quick Facts

DeveloperResolve AI
Websiteresolve.ai
Agent typeAI site reliability engineering (SRE) agent
Best forEngineering and platform teams at software companies with complex production systems and busy on-call rotations.
Not ideal forSmall teams with simple infrastructure, or buyers who need published self-serve pricing.
Pricing modelCustom quote
Starting priceCustom quote
Pricing detailsNo public pricing; sales-led.
Free planNo
Free trialDemo on request
ChannelsSlack, Microsoft Teams, web app
What it does on its ownInvestigates alerts and incidents on its own across connected tools and proposes root causes and fixes; engineers stay in control of changes.
IntegrationsDatadog, Grafana, Prometheus, Splunk, New Relic, AWS, Google Cloud, Azure, Kubernetes, GitHub, GitLab, PagerDuty, Opsgenie, ServiceNow, Slack, Microsoft Teams
PlatformsWeb (SaaS)
Compliance and securitySAML SSO, role-based access, redaction and retention controls; vendor says customer data is not used to train models for others.
Company founded2024
Details last verified29 October 2026
CategoriesEnterprise, IT & DevOps
User ratingNo reviews yet

In a case study published by Resolve AI, Coinbase reports 72% faster incident investigations and a time to root cause of under 10 minutes. The product acts as an AI site reliability engineer: when something breaks in production, it digs through logs, metrics, code changes and infrastructure to work out why.

Former Splunk executives Spiros Xanthos and Mayank Agarwal started the company in early 2024. In February 2026 it confirmed a $125 million Series A at a $1 billion valuation.

How It Works

Resolve AI connects to the tools a production stack already uses. Its integration list runs from Datadog, Grafana and Splunk to AWS, Kubernetes, GitHub, PagerDuty and ServiceNow. When an alert fires, teams of agents investigate in parallel, check recent deployments, compare telemetry and report likely causes with the evidence behind them.

Engineers can talk to it in Slack or Microsoft Teams during an incident, ask follow-up questions and have it draft fixes. It also connects to coding tools such as Claude, Codex and Cursor so that production context reaches the developer writing the fix. Beyond incidents, teams can set up custom agents for routine operational work, such as checking a service’s health after a release or answering a developer’s question about how a system behaves in production.

Pricing

Resolve AI does not publish prices. Deals are sales-led, and prospective customers book a demo rather than signing up for a free tier or self-serve trial. Expect enterprise-style contracts sized to the company’s infrastructure, incident volume and team. When comparing quotes, ask how usage is measured, whether the coding-tool connections and custom agents cost extra, and what onboarding help is included.

What to Watch Out For

An AI SRE is only as good as the data it can reach. Companies with patchy logging or tracing will see weaker results. The security page lists SSO, role-based access and data scoping, but the pages reviewed name no certifications such as SOC 2, so ask for audit reports. Decide early which actions the agent may take on its own and which need human sign-off. The AI SRE field is crowded, so run a side-by-side trial on real incidents.

Recent News

On February 4, 2026, TechCrunch reported that Resolve AI confirmed a $125 million Series A led by Lightspeed at a $1 billion valuation, with Greylock and Unusual Ventures also investing.

Features

  • Autonomous incident investigation across logs, metrics and traces
  • Root-cause analysis tied to code and deployment changes
  • Teams of agents working an incident in parallel
  • On-call help inside Slack and Microsoft Teams
  • Custom agents for recurring operational tasks
  • Connections to coding tools such as Claude, Codex and Cursor

Pros and Cons

Pros

  • Very broad integration list across observability, cloud and code
  • Founders built and sold an observability company before
  • Customer results reported at Coinbase, including faster investigations
  • Strong funding, with a $1 billion valuation

Cons

  • No public pricing
  • Aimed at large engineering organizations
  • No compliance certifications listed on the pages reviewed
  • Value depends on how well a company's telemetry is instrumented

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