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Cleric
Categories: Automation / Agents, Coding & Developer Tools, Customer Support |
Pricing: From $700/month |
Official Website ↗
Cleric uses AI agents to prevent production incidents by checking changes, fixing regressions, and automating alert responses for engineering teams.
Cleric is an AI-powered platform designed to prevent production incidents. It deploys AI agents that monitor every production change, identify regressions, and propose fixes before customers are impacted. The system also handles alerts, triages issues, dismisses false positives, and suggests solutions, reducing the burden on on-call engineers.
The platform integrates with existing development and operations stacks, learning from past investigations and continuously improving its ability to diagnose and resolve problems. Cleric aims to provide a comprehensive solution for SRE and observability, allowing engineering teams to ship code with greater confidence and focus on new development rather than incident response.
Key functionalities include change verification, where Cleric monitors releases for up to 14 days post-deployment, and automated incident response, where it investigates alerts, identifies root causes, and generates fix pull requests for approval.
Key Features
- AI agents for production monitoring
- Change verification (up to 14 days post-deploy)
- Automated incident triage and investigation
- Root cause analysis with evidence
- Fix recommendation (generates PRs)
- On-call automation (dismisses false positives)
- Operational memory and investigation history
- Custom agents and alert routing
Pros
- Prevents incidents by detecting and fixing regressions proactively.
- Reduces engineer workload by automating alert triage and investigation.
- Provides concrete fix recommendations with evidence.
- Learns and improves over time from past investigations.
- Integrates with common development and operations tools.
Cons
- Credit-based pricing can be complex to estimate for variable usage.
- Requires integration with existing production systems.
- Enterprise features like custom retention are only available on the highest tier.
- No explicit mention of support for all programming languages/frameworks.
- Relies on AI agent accuracy, which may have limitations.
Use Cases
- Automated change verification after code deployments
- Proactive detection and resolution of production regressions
- Reducing false positives in alert systems
- Automating incident response and root cause analysis
- Improving on-call engineer efficiency
Best For
- SRE teams
- DevOps engineers
- Platform engineers
- Engineering leaders
- Organizations seeking to reduce production incidents
Integrations: Slack, Microsoft Teams, Okta, Google Workspace, Cloudflare, Datadog, AWS Marketplace
Platforms: Web
Watch demo on YouTube ↗
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