Resolve AI

AI for production

March 2nd, 2026

Happy Monday.

We had a great time in SF last week. A room full of founders and even better conversations? Count us in, always.

We’ll be back soon. In the meantime, keeping you updated: we’re in Austin from March 14-19 for SXSW. Events we’re hosting (and RSVPs) are below. If you want to grab a coffee, respond to this email, and we’ll make it happen.

Arek and Ethan 🦄

  • Sunday, March 15 (Austin): We’re hosting an emerging managers + founding GPs dinner for 25 VCs at SXSW with Mercury and Sydecar. RSVP here.

  • ??? (Austin): 👀 

Resolve AI is building an AI companion for production code. Typically, engineers spend a nontrivial amount of time on remediating errors with code after it is deployed. When issues or incidents arise, they receive pager notifications, often at odd hours, and respond by diagnosing what went wrong and shipping a fix. Resolve AI detects and triages production failures early, investigates potential root causes, and suggests solutions to remediate such incidents. By focusing on reducing firefighting, it aims to save companies money and time by addressing alerts proactively and freeing engineering capacity.

Check it out: resolve.ai

The company’s pricing model varies by a customer’s scale and specific use case. It offers task-based pricing on an annual basis, where a task could be a chat with Resolve AI, an investigation session, or another action. In other words, this means customers pay a certain sum to use Resolve AI for a number of tasks per month.

Resolve AI is the third company CEO Spiros Xanthos and CTO Mayank Agarwal have built together. After meeting over 20 years ago in graduate school at the University of Illinois Urbana-Champaign, the two founded Log Insight, a tool designed to analyze machine-generated log data, which was acquired by VMware in 2012. Their next company, Omnition, was a leading contributor to OpenTelemetry and focused on observability tools like distributed tracing and improving monitoring across microservice applications before being acquired by Splunk in 2019. 

While at Splunk, the two frequently saw friction around alerting and incidents in production. Drawing on their broader industry experience, they felt the general inefficiency and pain around engineers on call in war rooms trying to assess and remediate issues, but it wasn’t until the recent improvement in LLM and AI capabilities that the duo decided they could finally tackle this problem effectively. 

From there, the founders built Resolve AI and launched in late 2024.

Fixing code after it's deployed to production is an inevitable, and inefficient, process. Most engineers are more interested in writing and shipping code than they are in being on call, handling incidents, and resolving errors. On top of that, in some companies, the process of investigating and fixing an issue can involve many different people, causing a general back-and-forth. 

Here’s what normally happens: incident alerts come in, suggesting that something is broken. Then, an army of engineers hops on a call, determines what went wrong, and discusses how to remediate the situation. This is nobody’s definition of fun, but everybody involved understands that there's a time sensitivity to troubleshooting and addressing issues that, if unresolved, have serious downstream consequences. 

Whether you’re an engineer with on-call horror stories or not, that’s a problem that’s pretty universal, painful, and important. 

Resolve AI addresses that by leveraging AI to better handle both alert investigation and incident remediation. Built on a multi-agent system, it uses source code, infrastructure, and observability tools for troubleshooting, working around the clock to respond to every alert. Effectively, it provides AI software reliability engineers who are always available and able to look into any issue, big or small, that gets flagged in production, working 24/7 the way a human can’t.

From initial investigation to using codebase-specific context to provide a root cause, Resolve AI will also provide proper documentation and a recommendation going forward to address the issue. In other words, for engineers, more tedious tasks that don’t require problem-solving (like documentation and messaging) are simplified. And for the truly complex production errors, Resolve AI provides a starting point on problem context and potential solutions, preventing the need to start from scratch. 

An example of an interaction with Resolve AI to solve a production deadlock.

While Resolve AI isn’t the only company in this space, it has two key advantages. First, its team has extensive experience in incident management and enterprise software resilience, gained through their two earlier startups and time at Splunk. Secondly, it uses that expertise to develop something more than a general wrapper around an LLM. Instead, it builds AI models and features specifically trained on enterprise codebases, which are often highly unique and context-specific. And its early momentum, demonstrated through a long list of reputable enterprise customers, suggests Resolve AI is not only solving the problem but doing so very effectively. 

After speaking with the team directly, we believe the founder fit here is as strong as it gets. The two founders not only have extensive experience with the pain points of this space, but with over 20 years of shared rapport and multiple successful startup exits, Agarwal and Xanthos understand their individual and combined strengths. That permeates through the rest of the company. For a startup still in its early stages, that chemistry and expertise between founders goes a long way. 

Resolve AI wants to solve how organizations approach on-call, with incident remediation as a more collaborative activity between AI agents and engineers and investigations remaining a more autonomous, AI-only pursuit. With a deep expertise in the problem space, early fundraising traction that has already hit unicorn status, and an incredibly strong founding team, Resolve AI is poised to be the premier solution that simplifies engineers' lives and improves production reliability. 

ICYMI: We recently announced our official investor syndicate. Check out the announcement post for more details on how to invest in our deals.

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