The alert always seems to fire at the worst hour. A deploy goes out, a queue backs up, and somewhere a phone starts buzzing on a nightstand. The engineer on call squints at Sentry, scrolls Datadog, greps a log, and eventually - bleary, annoyed - finds the one line that mattered buried under a hundred that didn't. Sonarly was built by two people who lived that routine enough times to decide a machine should do it instead.
Sonarly is a San Francisco company in Y Combinator's Winter 2026 batch, and its pitch is unusually literal: an AI engineer for production. It connects to the monitoring tools a team already runs, watches for alerts, and when one fires it does the work a human on-call would do - triage the noise, investigate the cause across logs, traces, metrics and code, and open a pull request with the fix. The company describes the goal as making software self-healing. The less poetic version is that it wants to shrink the time between "something broke" and "something is fixed."
01The bug you didn't write, at the hour you didn't want
Founders Dimittri Choudhury and Alexandre Klobb didn't arrive at this from theory. Their previous company, Meoria - an app they've described as "the Duolingo for finding schools" - reached more than 100,000 users in about six months and, in their telling, made them drop out to chase it. Running a consumer product at that scale meant living with the exhaust of production software: on some days, up to fifty Sentry alerts, most of them noise, a few of them real, and no fast way to tell which was which.
That is the quiet tax on most engineering teams. Alert fatigue is usually framed as a productivity problem, but it behaves more like a retention problem. When the signal is buried, real bugs live longer, and users feel the broken product before anyone gets around to the fix. Sonarly's founders decided the interesting work wasn't a prettier dashboard. It was removing the human from the boring middle of the loop entirely.
02Triage first, then let the agent loose
The temptation with any coding agent is to wire it straight to your alerts and hope. Sonarly's whole argument is that this doesn't work - and they have a number for it. A raw agent pointed at monitoring tools through generic connections lands the root cause about 53% of the time. Add Sonarly's triage layer and a running map of the system, and that figure climbs to 78%. The difference isn't a smarter model. It's the preparation that happens before the model reads a single line.
Underneath sits what the founders call a living map: a dynamically generated markdown model of a customer's production system, tracking services, dependencies, and the history of what has broken before. It is, effectively, the institutional memory an on-call engineer builds over months, handed to the agent on day one. When an alert fires, Sonarly doesn't start from scratch. It starts from a picture of how everything fits together.
03From a wall of alerts to a short list
The clearest way to understand what Sonarly does is to watch a bad deploy move through it. One customer, the company says, saw roughly 180 alerts from a single deploy collapse to about 50 unique issues after deduplication, then narrow to around 5 that were actually worth a human's attention. That is the part on-call engineers rarely get credit for and never enjoy: separating the five that matter from the hundred and seventy-five that don't.
04The new race to automate operations
Sonarly launches into a crowded and fast-moving corner of the market. There are AI-SRE startups like Cleric and Resolve AI aiming at the same on-call pain, and there is the do-it-yourself route of pointing a general coding agent at your monitoring tools. Sonarly's bet is that the winners won't be whoever has the flashiest agent, but whoever does the unglamorous work of triage and context best. In a field where everyone can call the same underlying models, the differentiator is what you feed them.
The business model is familiar developer SaaS. There's a free tier to get teams onboarded, a startup plan around $150 a month, and custom enterprise pricing, with a 14-day trial. Integrations - Sentry, Datadog, Grafana, Slack, Discord, Linear, GitHub, PagerDuty - connect through OAuth, and the setup is pitched at three minutes. The trial-and-expand shape is deliberate: land on the free plan, prove the fixes are real, grow with the team.
05Second-time founders, same instinct
Choudhury, who serves as CEO, moved from a small village in France to Paris to study computer science before the pair ended up in San Francisco for YC. Klobb brings the full-stack and ML engineering side. Their throughline is consistent: build things people actually use, ship quickly, and treat user feedback as the roadmap. It's the same "make something people want" instinct that carried Meoria to six figures of users, now pointed at a problem they know from the inside. The company operates under the parent name Mirabelle - a small yellow plum from the Lorraine region, a quiet nod home.
Whether an AI can genuinely own an on-call rotation is still an open question, and Sonarly is early - two people, a young batch, a handful of design partners. But the framing is sharp. Nobody wants "an agent." Everybody wants the 3am page to stop and the fix to be waiting in review by morning. Sonarly is selling the second thing, and hoping the first thing becomes true along the way.
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Watch: no official product-demo video was publicly available at publication. Check sonarly.com and the YC launch page for the latest walkthroughs.