Sazabi is an AI‑native observability platform that automatically creates actionable alerts without any configuration and surfaces only the incidents that matter. Engineers can query their systems in natural language to receive concise root‑cause explanations, visualizations, and remediation steps, while integrated AI coding agents can execute fixes directly from the chat interface. All telemetry—including logs, metrics, traces, code changes, and tickets—is unified into a single timeline for collaborative, context‑rich debugging.
Funding
Funding not disclosed
Founders
Product
Problem
Engineering teams spend excessive time configuring static alerts, navigating fragmented dashboards, and manually debugging production incidents, leading to alert fatigue, delayed issue resolution, and reduced system reliability.
Solution
Sazabi provides an AI-native observability platform that automatically generates actionable alerts without manual setup, learns baseline behavior, and surfaces only relevant incidents. Users can query their systems in natural language, receiving concise root‑cause explanations, visualizations, and remediation steps. The platform integrates tightly with major AI coding agents (e.g., Claude Code, Cursor, Codex), allowing agents to execute fixes directly from the chat interface. All telemetry—logs, metrics, traces, commits, and support tickets—is unified into a single timeline, enabling contextual insight and collaborative debugging. Sazabi continuously refines its models from each incident, building institutional memory that improves future alert relevance and diagnostic accuracy.
Target Audience
Primary customers are software engineering and DevOps teams at fast‑moving companies that require rapid incident response and continuous delivery pipelines.
Features
- Zero‑configuration autonomous alerts that adapt to evolving baselines and suppress noise
- Conversational debugging via plain‑language queries with dynamic charts, tables, and code snippets
- Integrated AI coding agents that can apply recommended fixes (e.g., updating Lambda timeouts) directly from chat
- Unified timeline correlating logs, metrics, traces, code changes, and support tickets
- Automatic error clustering and root‑cause identification with code‑level pinpointing
- Real‑time system status dashboard and multi‑channel alert delivery (Slack, PagerDuty, webhooks)
- CLI and SDK for rapid data source onboarding and log streaming from any environment