About
Superlog builds AI-native observability software for engineering teams, automatically instrumenting applications, grouping alerts into incidents, investigating failures, and preparing mergeable fixes. Its differentiation is a self-installing, vendor-neutral OpenTelemetry layer combined with an AI agent that investigates incidents and ships resolution pull requests directly through Slack.
Market
Superlog competes in cloud-native observability, application monitoring, and AI-assisted incident response. It positions itself as an open-core, local-first, agentic alternative to conventional monitoring platforms by automatically installing OpenTelemetry instrumentation, grouping telemetry into incidents, and proposing or opening fixes rather than merely generating alerts; its own comparison specifically contrasts this approach with Datadog and Sentry.
Superlog targets software product companies and engineering teams operating production web, mobile, or cloud-native systems, with a particularly strong fit for lean startup and mid-market development, platform, and SRE teams. Its self-installing instrumentation and automated remediation appeal to technical buyers who want observability without extensive setup or manual incident triage.
At a Glance
Problem
Superlog addresses the operational pain of conventional observability: tools such as Sentry and Datadog produce streams of duplicate alerts with insufficient context, leaving engineers to investigate and fix production issues manually. The cost is not only observability spend but also engineers’ nights and weekends, slower incident response, and lost revenue when a critical service fails. Its clearest use case is an incident such as a missing production Stripe credential taking checkout down: Superlog is intended to identify the underlying cause and produce a tested fix rather than merely notify the on-call team.
Product / Service
Superlog is an open-source, agentic observability system built around OpenTelemetry. An installation wizard scans a repository, adds structured logs, traces, metrics, and service instrumentation, and then runs recurring checks so telemetry, alerts, and dashboards keep pace with code changes. When failures occur, it fingerprints and groups noisy signals into incidents, assigns severity and impact, investigates using telemetry and deployment context, and posts a mergeable resolution pull request in Slack. The intended benefit is observability that requires little ongoing maintenance and can resolve routine bugs without opening another monitoring dashboard.
The delivery model is open-core: the Apache-licensed community edition provides the core telemetry and incident-management stack, while Superlog Cloud offers a hosted free tier and pay-as-you-go usage. The product is designed to remain vendor-neutral through OpenTelemetry, while charging for telemetry volume and AI investigations rather than imposing a conventional platform base fee.
Market
Superlog competes in AI-native observability, autonomous incident response, and developer tools, with an open-source and Kubernetes-oriented positioning. Its most direct established competitors are Sentry and Datadog, which it contrasts with on alert noise, setup burden, and the need for manual remediation; adjacent alternatives include HyperDX, Zipy, and Better Stack. Its differentiation is the combination of self-installing instrumentation, incident grouping, contextual investigation, and automated pull requests rather than alerting alone.
The company is an early-stage YC Spring 2026 startup listed as active, with a two-person team. Public traction is visible but primarily community and launch traction: the repository reports 1,058 GitHub stars, 79 forks, and 435 commits, while its June 3, 2026 Product Hunt launch ranked third of the day with 517 points. The public materials reviewed do not disclose customer counts or revenue, so Superlog should be treated as early commercial or possibly pre-revenue rather than as a company with demonstrated revenue traction.
Founders & Leadership
Funding History
Y Combinator
Recent News
Y Combinator featured Superlog’s launch and described its self-installing OpenTelemetry instrumentation, incident investigation agent, and mergeable fix PRs. The announcement positions Superlog as an observability tool designed to keep telemetry synchronized with a codebase and resolve production issues.
Superlog announced quieter incident handling, conversational follow-up through Slack and GitHub, agent memories and feedback, and the ability to open multiple PRs. It also announced one-click integrations for Cloudflare, Render, Vercel, and Railway, with GCP and Azure planned next.
Superlog’s public GitHub repository was created as an Apache-2.0 open-source agentic telemetry system that ingests traces, logs, and metrics and groups them into incidents. The repository also documents a hosted Superlog Cloud edition with a free tier and paid plans.
Superlog co-founder Arseniy Shishaev published an analysis based on conversations with more than 50 Seed and Series A CTOs, covering alert fatigue, observability debt, telemetry organization, and LLM costs. The article introduces Superlog as a tool that instruments code, investigates errors, and sends a Slack message with a fix PR.
Superlog was presented on Hacker News as an observability product that scans code and infrastructure, adds alerts and dashboards, groups errors into incidents, and prepares resolution PRs. The discussion also covered its OpenTelemetry architecture, sandboxed coding-agent workflow, and Slack-based incident handling.
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Get notified when they postBusiness Model
Superlog uses a subscription-plus-usage model. It offers a free tier, paid Pro and Max plans with monthly investigation credits, pay-as-you-go telemetry charges, and custom Enterprise pricing for higher volumes, security features, retention, and support.