Relvy

Overview

Relvy is an AI on-call engineer built for production environments. When an alert triggers, it automatically takes over the investigation, relying on a continuously updated context layer—including runbooks, historical troubleshooting memory, and real-time integrations with telemetry, code, and infrastructure—to deliver timely, well-founded diagnostic conclusions without starting from scratch.

Relvy's core strength lies in its Investigation Notebooks: every investigation produces structured, auditable, and visually rich records that team members can replay, review, and trust. It also supports plain-text Runbooks to guide investigation paths—whether importing existing documentation or having AI assist in authoring—so you can standardize your incident response process.

The platform includes specialized tools optimized for time-series data and massive-scale log analysis, and integrates seamlessly with leading observability, code, and infrastructure systems. Official data shows that 70% of alerts can be pinpointed within 5 minutes. Forward Deployed Engineers fine-tune the solution to your enterprise's specific tech stack. With SOC 2 Type II compliance and support for private deployment, Relvy meets the demands of large-scale enterprise SRE and platform engineering teams.

Core capabilities

Automated alert investigation

Autonomously analyzes telemetry data and code to pinpoint the root cause of alerts

Investigation notebook

Generates auditable, visual, and replayable troubleshooting records

Runbook support

Plain-text Runbooks guide investigations, and can be imported or AI-assisted

Context memory layer

Continuously updates historical troubleshooting experience to form prior knowledge

Deep integration

Seamlessly connects to logs, metrics, traces, code, and internal APIs

Dedicated performance tools

High-efficiency queries optimized for time-series data and million-scale logs

Standardized response

Promotes a unified incident handling process across teams

Enterprise-grade security

SOC 2 Type II compliant, with private deployment support

Use cases

When nocturnal alerts go unattended, Relvy automatically investigates and delivers a root-cause report

Quickly locate the specific service or dependency causing failures in a large microservices architecture

Codify senior engineers' troubleshooting experience into Runbooks so AI can replicate the same approach

Get an auditable investigation outcome within minutes after an alert fires in PagerDuty or similar channels

Help new engineers quickly learn the team's incident response process and troubleshooting mindset

During post-incident reviews, replay the investigation notebook to reconstruct the full timeline and decision rationale

Reduce context-switching costs between teams through a standardized investigation workflow

In private deployments, provide secure incident response for highly regulated industries like finance and healthcare