Cleric AI is an AI-powered engineering assistant built to support on-call developers and SaaS teams by helping them triage, debug, and resolve incidents faster. Designed as a copilot for production engineering, Cleric connects directly with your tools—logs, codebase, infrastructure, and observability platforms—to provide contextual answers, suggest fixes, and automate repetitive incident response tasks.
Modern software teams face growing complexity in their tech stacks and increasing pressure to reduce mean time to resolution (MTTR) during outages and on-call shifts. Cleric aims to eliminate alert fatigue and reduce context switching by acting as a smart first responder that integrates into Slack and GitHub, enabling developers to resolve issues in minutes instead of hours.
Whether you’re an SRE, DevOps engineer, or backend developer, Cleric helps you stay focused on building, while it handles the grunt work of parsing logs, understanding system behavior, and recommending actions.
Features
1. Slack Integration for Real-Time Support
Cleric works inside Slack, where engineering teams already live. Just ask a question about an incident, and Cleric responds with context-aware answers.
2. On-Call Triage Assistant
Cleric summarizes alerts, provides suggested root causes, and connects the dots between logs, code changes, and recent deploys.
3. Codebase Understanding
Integrated with GitHub, Cleric can explain how functions work, identify related pull requests, or find when a line of code was last modified.
4. Log Intelligence
Cleric scans logs and surfaces relevant entries based on your query or the nature of the alert, reducing the time engineers spend digging through raw data.
5. Incident Summarization
Get AI-generated summaries of incidents that include key events, affected services, timestamps, and suggested resolutions.
6. Works with Popular Tooling
Cleric integrates with tools like Datadog, PagerDuty, GitHub, and Slack to fetch the necessary context for incident resolution.
7. Secure and Private
Engineered with enterprise security in mind, Cleric runs in a sandboxed environment and does not store logs or code beyond what’s needed for analysis.
How It Works
Step 1: Connect Your Stack
Link Cleric to your Slack workspace, GitHub repositories, and observability tools such as Datadog or PagerDuty. This gives Cleric access to your system’s signals.
Step 2: Ask Questions in Slack
Developers can ping Cleric in a Slack channel and ask natural language questions like “What caused the 500 errors last night?” or “What did the last deploy change?”
Step 3: Cleric Analyzes and Responds
Cleric uses AI to parse logs, correlate code changes, and reference monitoring alerts to respond with concise, actionable answers.
Step 4: Take Action or Escalate
Use Cleric’s suggestions to fix issues directly, or escalate with a deeper understanding of what went wrong and where to look.
The entire process is designed to feel like having a senior engineer on-call, ready to assist 24/7.
Use Cases
1. Incident Response
Reduce MTTR by getting fast context and suggestions during production incidents, directly in Slack.
2. On-Call Support
Support junior engineers or teams with minimal ops experience by giving them an always-available assistant during off-hours.
3. Codebase Exploration
Ask Cleric questions about specific files, functions, or history to understand code ownership, last changes, or purpose.
4. Postmortem Summaries
Generate incident retrospectives with AI summaries of what happened, when, and how it was resolved.
5. Continuous Learning
New engineers can query Cleric to get familiar with the system’s behavior, previous issues, and architectural design.
Pricing
As of June 2025, Cleric AI operates on a request-based pricing model, primarily targeting engineering teams and SaaS companies. Pricing details are available upon request through the sales team.
Current Offerings:
Free Trial (Available on Request):
Limited number of Slack queries
Basic integration setup
Access to incident triage and log parsing
Team Plan (Contact for Pricing):
Unlimited Slack usage
Full GitHub and observability tool integration
Advanced incident summarization
Priority support
Enterprise Plan:
SOC 2 and GDPR-compliant deployment
Dedicated support engineer
On-premise or VPC deployment
Role-based access controls
SLA-backed support
To inquire about pricing or start a trial, visit https://cleric.ai
Strengths
Purpose-Built for Engineers: Cleric understands engineering workflows and offers tailored responses for real debugging and production issues.
Slack-Native Experience: Seamless integration into Slack keeps developers focused and reduces tool switching.
Contextual Intelligence: Combines logs, code, and observability into one AI-driven assistant.
Time-Saving Automation: Reduces triage time and supports faster resolutions without paging more engineers.
Private and Secure: Built with data privacy in mind, with enterprise-grade security features.
Drawbacks
Requires Integration Setup: Teams need to connect multiple tools for full benefit, which may take time initially.
Slack-Dependent Interface: Currently optimized for Slack users; limited support for other platforms like Microsoft Teams.
AI Limitations: Like any AI assistant, responses may require human validation, especially in critical incidents.
Pricing Transparency: No public pricing tiers may deter smaller teams or startups evaluating cost upfront.
Comparison with Other Tools
Cleric AI vs. PagerDuty AIOps:
PagerDuty offers automated alert management but lacks conversational AI assistance. Cleric brings natural language interactions directly into Slack.
Cleric AI vs. ChatGPT in Slack:
Generic GPT tools require manual prompting and lack system integration. Cleric understands your stack and gives context-aware answers.
Cleric AI vs. Opsgenie or Splunk On-Call:
While these tools handle alert routing, Cleric helps with triage and resolution—focusing on understanding the issue, not just notifying it.
Cleric AI vs. Code Search Tools:
Unlike source search tools like Sourcegraph, Cleric adds reasoning, log context, and conversational summaries for a more holistic debugging aid.
Customer Reviews and Testimonials
Cleric is gaining popularity among mid-size SaaS companies and platform engineering teams. Here’s what early adopters are saying:
“Cleric shaved 50% off our MTTR. It’s like having a senior engineer on every shift—even weekends.” – Head of DevOps, SaaS Company
“I got a Slack message about 502 errors. Cleric had already linked the logs and the relevant deploy. It’s magical.” – On-call Engineer
“We now include Cleric in our incident retros. Its summaries make our postmortems faster and more actionable.” – Engineering Manager
Cleric continues to receive praise for helping reduce alert fatigue, accelerate onboarding, and streamline operations.
Conclusion
Cleric AI is redefining incident response and engineering operations by giving teams a smart, always-available assistant that lives in Slack and understands your entire tech stack. It transforms how developers interact with logs, code, and alerts—making debugging faster, smoother, and less stressful.
For SaaS companies looking to reduce on-call burnout, improve MTTR, and empower their teams with AI-driven insights, Cleric offers a future-ready solution that fits right into your existing workflows.
