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Automatically root cause on-call issues

Struct is an AI support engineer that cross-references logs, metrics, traces, and your codebase to accurately root-cause engineering alerts and bugs — before you start debugging. Trigger an investigation by @mentioning Struct in Slack, assigning an issue in Linear or Asana, or letting Struct respond automatically to alerts in your connected channels.
Struct completes its investigation before you open your laptop. Get started free — no credit card required.

How It Works

1

Integrate

Connect your observability stack, cloud logs, and codebase in minutes. Struct integrates with Sentry, Datadog, AWS, GitHub, Slack, and more.
2

Investigate

For every alert, Struct gathers logs, metrics, and traces — cross-references your codebase and recent commits — and delivers a structured root cause report.
3

Dive Deeper

Ask follow-up questions, explore alternative hypotheses, and query your production systems in natural language with Ask Struct.
4

Fix or Hand Off

Create a PR with one click, or hand off to your coding agent (Claude Code, Cursor) with full investigation context.

Key Capabilities

Cross-Signal Correlation

Queries logs, metrics, traces, and your codebase in parallel — then connects the dots across systems.

On-Call Intelligence

Learns from past alerts and investigations to recognize patterns and improve accuracy over time.

Ask Struct

Ask questions in natural language across all your production systems. No more switching between dashboards.

Fix & Handoff

One-click PRs with the Build Agent, or seamless handoff to Claude Code and Cursor via MCP.

Get Started

Quickstart

Sign up free and run your first investigation in minutes

Connections

Connect your observability stack, cloud logs, and tools

Ask Struct

Query your production systems in natural language

Open in Claude Code / Cursor

Set up MCP server and CLI bridge for one-click handoff

Security

SOC2 Type II

Fully compliant with SOC2 Type II standards

HIPAA Compliant

Meets HIPAA requirements for protected data
  • All data encrypted in transit and at rest
  • Logically isolated per customer
  • No customer data used for model training
Trust documentation available at trust.struct.ai