PagerDuty

AI-powered incident management in Slack and Teams

Rootly is an AI-native incident management platform that runs entirely within Slack and Microsoft Teams, automating incident workflows from detection through postmortem. It reduces manual incident overhead with AI-generated summaries, automated role assignments, escalation paths, and postmortem drafts, holding SOC 2 Type II, GDPR, and HIPAA compliance certifications for enterprise use.

Slack-native incident management with AI SRE agent

Incident.io is a Slack- and Microsoft Teams-native incident management platform with AI SRE investigation, on-call scheduling, status pages, and post-incident learning in one product. Vendor case studies cite Buffer reducing critical incidents by 70% and Favor reducing MTTR by 37%. It integrates with PagerDuty, Datadog, GitHub, Jira, and 100+ tools for incident response and operational workflows.

Open-source SOAR platform with AI-powered playbooks

Tracecat is a YC S24-backed open-source SOAR (Security Orchestration, Automation and Response) platform that lets security teams build AI-powered playbooks for automated incident response. It provides visual workflow builders for creating response procedures, integrates with common security tools, and handles alert triage, enrichment, and remediation — positioned as an open-source alternative to Tines and Splunk SOAR.

Sentry-style observability for AI agent conversations

Latitude is an agent observability platform for teams that need to inspect LLM traces, conversations, issues, and evaluation feedback in one workflow. Its public repo and docs position it as a Sentry-style monitor for AI agents, with semantic search, issue detection, annotations, MCP-assisted fixes, and cloud or self-hosted deployment paths for production debugging.

Session reports for Claude Code and Codex runs

Spotlight by Backplanes turns completed Claude Code and Codex sessions into concise reports for engineering, security, and spend review. The CLI installs on macOS, Linux, or WSL 2, watches sessions after they finish, redacts PII and credentials locally before upload, then summarizes files touched, commands run, external domains reached, scope drift, risky actions, and next-session improvements.

OpenTelemetry-native observability with AI tracing, logs, traces, metrics, and session replay — self-hosted in 90 seconds.

Traceway is an open-source, OpenTelemetry-native observability platform that combines logs, traces, metrics, exceptions, session replay, and AI tracing in a single self-hosted system. MIT licensed with no open-core restrictions, it deploys in 90 seconds via Docker Compose and accepts OTLP/HTTP from any OTel SDK without a Collector or per-language vendor SDK.

Open-source post-building layer for agents — tracing, evals, and online monitoring

Judgeval is the open-source post-building layer for AI agents from Judgment Labs, providing OpenTelemetry-based tracing, hosted and custom evaluation scorers, and online behavior monitoring for LLM-powered applications. Instrument any function with a single decorator, score live production traffic against faithfulness and instruction-adherence checks, and feed real-world failures back into reinforcement learning or supervised fine-tuning loops.

Open-source observability and self-healing layer for AI agents

TraceRoot is a YC S25-backed open-source observability platform purpose-built for AI agents and LLM apps. It combines OpenTelemetry-compatible tracing with an agentic debugging runtime that reads your source code, correlates failures with recent commits, and proposes fix PRs automatically. BYOK support spans seven LLM providers; the entire stack runs self-hosted via Docker Compose, with TraceRoot Cloud available for managed deployments.

Open-source toolkit for building AI SRE incident response agents

OpenSRE is Tracer Cloud’s open-source public-alpha Python toolkit for building AI SRE agents that investigate and respond to production incidents. It ships 60+ tools across observability, databases, incident management, communications, deployment and protocol integrations, plus simulation/evaluation workflows for benchmarking agent accuracy before live pager use.