# Catch and fix bad deploys before they escalate

> Cleric links errors and performance issues to the deploy that caused them.
>
> Markdown version of https://cleric.ai/solutions/deployment-failures for AI agents and LLMs. Site index: https://cleric.ai/llms.txt

Solutions / Debug Deployment Failures. Cleric is an autonomous AI SRE that helps engineering teams quickly diagnose production issues in complex cloud-native environments.

## What Cleric does

### Instant Analysis

Starts investigating the moment a deployment-related alert fires from your CI/CD pipeline or observability tools.

### Hypothesis-Driven

Tests possible causes across code, config, and infrastructure, linking issues like error spikes or latency to the specific deploy.

### Clear Deliverable

Delivers a concise diagnosis with evidence and specific fix recommendations (e.g., revert a config change) to Slack or Microsoft Teams, tagged to the right owner.

## How Cleric stands out

### Root Cause to Deploy

Connects failures directly to the source change in your CI/CD pipeline.

### Covers App + Infra

Handles issues from application regressions to infrastructure misconfigurations.

### Deploy-Aware Reasoning

Understands what changed and when, ensuring fast and accurate diagnoses.

## Common incidents handled

- Failed Deployments (code, config, infra)
- Application Error Spikes (HTTP 5xx, gRPC)
- Memory Leaks introduced post-deploy
- Scaling Bottlenecks under load
- Ingress & Gateway Errors
- Kubernetes Config Errors

## Your AI SRE is ready for duty

Cleric investigates every alert like your most experienced engineer: always available, always contextual, ready in Slack or Microsoft Teams.

- Connects metrics, logs, and changes instantly
- Identifies root causes with ranked evidence
- Learns and maps your systems over time
- Remembers past incidents to solve new ones

- Start free trial: https://cleric.ai/start
- Explore the product: https://demo.cleric.ai
- Book a demo: https://cleric.ai/demo