How does Struct handle alerts from multiple services in complex architectures?

Struct uses encoded correlation techniques, such as querying by correlation IDs, to string together logs across different services from various observability providers. It constructs a unified timeline and iteratively digs deeper to establish definitive root causes, making it effective for distributed systems.

Is Struct compliant with security and privacy standards?

Yes, Struct is fully SOC 2 Type II and HIPAA compliant, ensuring that data security and privacy are maintained for sensitive information and regulated industries.

How long does it take to set up and deploy Struct?

Struct can be set up in as little as 5 to 10 minutes, with no credit card required for the free tier. It avoids lengthy sales cycles and heavy enterprise projects, delivering immediate value.

Does Struct require manual intervention during incidents?

No, Struct proactively starts investigations automatically when alerts fire, unlike reactive LLMs that need manual prompts. This allows it to complete analyses before engineers even engage, reducing response time.

What integrations does Struct support for existing workflows?

Struct integrates with every leading observability platform (e.g., Datadog, Sentry, GCP, Azure), plus collaboration tools like Slack, GitHub, Linear, and Claude Code, fitting seamlessly into DevOps workflows without disruption.

Struct

AI agent that root-causes engineering alerts

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What is Struct

Struct is an AI-driven platform that automatically investigates and root-causes engineering alerts by analyzing logs, metrics, traces, and code. It enables faster incident resolution through proactive investigations triggered when alerts fire, integrating seamlessly with existing DevOps tools like Slack and Datadog. Designed for lean teams and scalable deployments, it reduces manual triage time and enhances on-call efficiency.

Key Features

Automated root cause analysis triggered by alerts, starting proactively without manual prompts

Integration with leading observability platforms (e.g., Datadog, Grafana) and collaboration tools (e.g., Slack, GitHub)

Quick deployment and setup in minutes, with no long sales cycles or complex configurations

Dynamic investigation dashboards with visual evidence and unified timelines

Customizable workflows that adapt to unique architectures and memorize successful debugging techniques

Use Cases

Startups and lean engineering teams without dedicated SREs to automate incident triage and reduce on-call burden
Companies with complex microservices architectures needing to correlate logs and metrics across multiple services for faster root cause identification
Engineering teams aiming to reduce manual log-hunting and alert investigation, cutting triage time by up to 80%
Organizations under strict SLAs requiring rapid incident resolution and compliance with security standards like SOC 2 and HIPAA
Teams wanting to empower junior engineers to handle on-call duties confidently with AI-assisted insights

Why do startups need this tool?

Startups often operate with lean engineering teams lacking dedicated SREs, making incident management a time-consuming distraction from product development. Struct provides a fast, scalable solution that reduces triage time by up to 80%, enabling engineers to focus on innovation rather than reliability firefighting. Its quick setup and broad integrations allow startups to achieve immediate operational efficiency without costly implementation projects.