Sazabi releases version 1.0 of its AI monitoring tool, which reads logs and sends investigated alerts for teams shipping code with agents
Today, we're launching Sazabi version 1.0. The reality of shipping software as a team in the age of AI is actually crazy. Agents merging their own PRs. Hundreds of deployments per day. A codebase that is constantly changing. Junior developers with 10x or 100x leverage. 😵💫 I spent the last year building a safety harness for teams that ship with AI. It's called @sazabi. The premise is simple: 1. You send us logs. 2. We detect anomalies, investigate them, and send you back rich, actionable alerts about real problems in your app. Sazabi helps you find issues before your users notice. No monitors or noisy alerts. Just pure signal. And today we're making it available for anyone to use.
Context
When agents merge their own code and teams deploy hundreds of times a day, catching problems before users do becomes harder, creating demand for AI native monitoring.
Sherwood Callaway is the founder of Sazabi, a Y Combinator company, so this is a first hand launch post. Sazabi previously announced an $8 million seed round and an open beta on its blog. Claims about the product come from the company.
Deep dive
On October 13, Sherwood Callaway posted: Today, we're launching Sazabi version 1.0.
He wrote that shipping software as a team in the age of AI is actually crazy, listing agents merging their own pull requests, hundreds of deployments per day, a codebase that is constantly changing and junior developers with 10x or 100x leverage. He said he spent the last year building a safety harness for teams that ship with AI.
He described the premise: customers send Sazabi their logs, and it detects anomalies, investigates them and sends back rich, actionable alerts about real problems in the app. He wrote that it helps teams find issues before users notice, with no monitors or noisy alerts, just pure signal, and that it is now available for anyone to use.
Sazabi's Y Combinator launch page pitches it as Datadog for the AI era, using logs, code and infrastructure data to find anomalies and their root causes. The company earlier ran an open beta after its $8 million seed round, so version 1.0 marks general availability rather than a first release.
Anthropic's report the same day of merging over 30,000 code changes a day, in story 17, shows the kind of pressure such tools are built for.
What to expect next
Watch whether Sazabi can win customers from established monitoring companies such as Datadog, which are adding their own AI investigation features.
Also watch how well its automatic alerts avoid false alarms in real use, since cutting noise is the core promise. Customer case studies showing problems caught before users noticed them would be the clearest proof of its value for teams that ship with agents.