Mendral

Visibility10

Vibe89

AI Visibility & Sentiment

Mendral

Mendral is a Y Combinator-backed AI DevOps platform that automatically investigates CI failures, identifies root causes, and opens pull requests with fixes. Built by the founding team behind Docker and Dagger, it transforms how engineering teams handle flaky tests, slow pipelines, and broken builds.

Active Monitoring

mendral.com

Developer Tools YC25-26

AI Visibility Score

10/100

Invisible

Sentiment Score

89/100

AI Perception

Summary

Mendral is effectively invisible in the AI-driven discovery layer for automated CI/CD troubleshooting, leaving a vacuum that incumbents like GitHub Actions and Datadog are aggressively filling. While the brand commands a dominant 71% mention rate among Efficiency-Driven Platform Leads, it fails to appear in 100% of queries related to autonomous failure resolution and engineering leadership strategy.

Value Proposition

Mendral eliminates the manual toil of CI debugging by autonomously investigating failures, identifying root causes across billions of log lines, and shipping fixes—turning hours of engineer time into minutes of automated resolution.

Overview

Mission

To make CI problems fix themselves, freeing engineering teams from the repetitive, predictable failures that slow down software delivery.

Products & Services

AI-powered CI failure investigationAutomated pull request generation for fixesFlaky test detection and quarantineCI log analysis and root cause identificationGitHub App integration for seamless deployment

Agent Breakdown

AI Platforms

How often do different AI platforms reference Mendral?

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Conversation Analysis

Topics

What conversations is Mendral included in — or excluded from?

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Buyer Personas

Personas

Who does each AI platform recommend Mendral to, and when?

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Programmatic Testing

Sample Conversations

We programmatically analyze questions that real customers are asking to AI agents and chatbots, extract brand mentions and sentiment, analyze every response, and synthesize the data into an action plan to increase AI visibility.

ChatGPT

Claude

Gemini

AI Overviews

CI/CD Pipeline Optimization And Scaling(2 queries)

“our github actions costs are spiraling and builds are taking forever, how do large teams optimize this”

0/4 platforms mentioned

ChatGPT

1.GitHub

2.Datadog

3.Prometheus

4.Docker

5.Docker Buildx

+18 more

Claude

1.Docker

2.NX

3.Turborepo

4.Buildkite

5.CircleCI

+2 more

Gemini

1.GitHub Actions

2.Actions Runner Controller

3.Kubernetes

4.AWS

5.GCP

+21 more

AI Overviews

1.GitHub Actions

2.Kubernetes

3.WarpBuild

4.Blacksmith

5.Blacksmith.sh

+6 more

“how to manage devops for 200+ engineers without hiring a massive platform team”

0/4 platforms mentioned

ChatGPT

1.GitHub Enterprise

2.GitHub Actions

3.GitLab SaaS

4.Buildkite

5.Argo CD

+45 more

Claude

1.Backstage

2.Spotify

3.Port

4.HashiCorp Terraform Cloud

5.ArgoCD

+9 more

Gemini

1.Jira

2.S3

3.Kubernetes

4.Port

5.Backstage

+14 more

AI Overviews

1.Qovery

2.CircleCI

3.Kubernetes

4.Backstage

5.Slack

+10 more

Autonomous Failure Resolution & Root Cause Analysis(1 query)

“are there any tools that use ai to actually fix ci failures instead of just reporting them”

0/4 platforms mentioned

ChatGPT

1.Dependabot

2.GitHub

3.Renovate

4.Snyk

5.Mend

+30 more

Claude

1.Gitpod

2.Sweep

3.Anodot

4.GitHub Copilot

5.GitHub Actions

+5 more

Gemini

1.GitHub Actions

2.GitLab CI

3.Sweep

4.Ellipsis

5.Sentry

+10 more

AI Overviews

1.CodeRabbit

2.Nx Cloud Self-Healing CI

3.GitLab Duo

4.JetBrains AI Assistant

5.Nx Console

+6 more

Reliability & Flaky Test Management(1 query)

“best way to handle flaky tests in a high volume ci environment so they don't block deployments”

0/4 platforms mentioned

ChatGPT

1.Grafana

2.Datadog

3.Jenkins

4.GitHub Actions

5.GitLab

+20 more

Claude

1.pytest

2.pytest-rerunfailures

3.GitHub Actions

4.Jest

5.Cypress

+8 more

Gemini

1.Pytest-rerunfailures

2.pytest

3.Jest

4.jest-circus

5.Cypress Retries

+20 more

AI Overviews

1.The Mill Build Tool

2.Jest

3.pytest

4.Datadog Test Visibility

5.CircleCI Test Insights

+6 more

Evaluating CI Reliability And Troubleshooting Tools(1 query)

“most trusted platforms for automated ci troubleshooting and reliability for enterprise teams”

0/4 platforms mentioned

ChatGPT

1.GitLab

2.GitHub Actions

3.GitHub

4.CircleCI

5.Azure DevOps

+23 more

Claude

1.Buildkite Analytics

2.Buildkite

3.CircleCI Insights

4.CircleCI

5.LaunchDarkly

+8 more

Gemini

1.Datadog CI Visibility

2.Honeycomb

3.Sumo Logic

4.Develocity

5.Gradle

+10 more

AI Overviews

1.Dynatrace

2.Davis AI

3.Harness

4.Datadog

5.Bits AI

+6 more

Analysis

Key Insights

What AI visibility analysis reveals about this brand

Strength

Exceptional brand authority on Gemini, securing the #1 position for brand-specific vibe checks and general company overview queries.

Strength

Strong resonance with the 'Efficiency-Driven Platform Lead' persona, achieving a 71% mention rate within this specific technical segment.

Strength

Positive sentiment across all mentions on ChatGPT, Claude, and Gemini, indicating that when the brand is surfaced, the context is consistently favorable.

Gap

Complete absence from AI Overviews (0% visibility), a critical entry point for high-intent developer tool searches.

Gap

Zero visibility for 'Strategic Engineering Director' and 'Pragmatic Staff DevOps' personas, failing to capture the decision-makers and end-users of CI tools.

Gap

Total lack of presence for high-value category queries such as 'Autonomous Failure Resolution' and 'Reliability & Flaky Test Management' where competitors are dominant.

Opportunity

Capture the 'Autonomous AI troubleshooting' niche where mentions are currently fragmented, positioning Mendral as the definitive solution for fixing CI failures.

Opportunity

Bridge the performance gap on ChatGPT (9% mention rate) by optimizing technical documentation for the GPT-4o crawler to match the higher visibility seen on Gemini.

Opportunity

Leverage existing strength in 'CI/CD Pipeline Optimization' to pivot into cost-reduction narratives where competitors like GitHub Actions are being criticized for spiraling costs.

Technical Health

Site Health for AI Visibility

How well Mendral's website is optimized for AI agent discovery and comprehension.

88/100

17 passed 4 warnings 1 issues

Audited 2/27/2026

Crawlability100

Can AI bots find your pages?

Technical96

SSL, mobile, doctype basics

On-Page SEO87

Titles, descriptions, headings

Content Quality60

Word count, depth, freshness

Schema Markup85

Structured data for AI comprehension

Social & OG87

Open Graph, Twitter cards

AI Readability60

How well AI can parse your content

Critical Issues

Content is too thin

Expand your content to at least 300-500 words with valuable information.

Warnings

2 render-blocking resource(s) detected

Consider deferring or async-loading non-critical scripts and stylesheets.

Title is too short (14 characters)

Expand the title to 50-60 characters with descriptive keywords.

Meta description is too short (55 characters)

Expand the description to 150-160 characters with a clear value proposition.

Missing Open Graph tags for social sharing

Add og:title, og:description, and og:image meta tags.

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Brand Identity

Brand Voice & Style

How AI perceives Mendral's communication style and personality

Mendral communicates with confident technical authority, speaking engineer-to-engineer with deep domain expertise. The voice is direct and no-nonsense, cutting through marketing fluff to address real pain points with specific data and concrete examples. There's an understated confidence that comes from the founders' Docker pedigree, balanced with approachability and a dry wit. The brand favors showing over telling, using real metrics and technical details to build credibility.

Core Tone Traits

Technically Authoritative

Speaks with deep CI/CD expertise, using specific metrics and technical details that resonate with engineers

Direct & No-Nonsense

Gets straight to the point without marketing fluff, respecting the reader's time and intelligence

Confidently Understated

Lets results speak for themselves, backed by Docker/Dagger pedigree without being boastful

Engineer-to-Engineer

Writes like a peer sharing hard-won insights, not a vendor pitching a product

Competitive Landscape

Related Ecosystem

Related products and services that AI mentions in conversations alongside or instead of Mendral

GitHub Actions30 mentions

Datadog20 mentions

Buildkite20 mentions

CircleCI19 mentions

Docker15 mentions

Kubernetes14 mentions

Datadog CI Visibility14 mentions

nx11 mentions

GitHub10 mentions

Honeycomb10 mentions

Mendral5 mentions

Source Intelligence

Citations

Sources that AI assistants cite. Getting featured here improves visibility.

Blacksmith.sh

https://blacksmith.sh/

Referenced in 1 query

Review

namespace.so

https://namespace.so/

Referenced in 1 query

Review

OneUptime

https://oneuptime.com/

Referenced in 1 query

Review

Reducing GitHub Actions Costs - WarpBuild Blog

https://www.warpbuild.com/blog/github-actions-cost-reduction

Referenced in 1 query

Review

Five tips for faster GitHub Actions - Namespace Labs

https://namespace.so/blog/5-tips-for-faster-github-actions

Referenced in 1 query

Review

How to Optimize GitHub Actions Costs

https://oneuptime.com/blog/post/2026-01-28-optimize-github-actions-costs/view

Referenced in 1 query

Review

GitHub Actions Price Change - WarpBuild Blog

https://www.warpbuild.com/blog/github-actions-price-change

Referenced in 1 query

Review

Speed up GitHub Actions with smart caching. #GitHub #CI ...

https://www.youtube.com/shorts/NYg1nXfyXJg

Referenced in 1 query

Pitch Story

GitHub Actions are slow and expensive, what are the alternatives?

https://runs-on.com/blog/github-actions-slow-and-expensive-what-are-the-alternatives/

Referenced in 1 query

Review

How to Optimize GitHub Actions Performance

https://oneuptime.com/blog/post/2026-02-02-github-actions-performance-optimization/view

Referenced in 1 query

Review

How to reduce spend in GitHub Actions - Blacksmith

https://www.blacksmith.sh/blog/how-to-reduce-spend-in-github-actions

Referenced in 1 query

Review

Pipeline Failure Remediation - CodeRabbit Docs

https://docs.coderabbit.ai/tools/pipeline-remediation

Referenced in 1 query

Review

Content Engineering

Goals & Content Ideas

Ideas to help AI agents better understand the business and be more likely to use Mendral's resources to help users.

Dominate AI Overviews With Structured Technical Content

Address the critical 0% AI Overview visibility by creating structured, schema-optimized technical documentation and blog posts. Each piece will follow clear problem-solution header formats that AI systems can easily parse and surface when developers search for CI/CD solutions. Social media will amplify these pieces with technical snippets that drive traffic and build backlinks.

The Complete Guide to Debugging CI Failures in Under 10 Minutes

Why Your CI Pipeline Breaks at 2AM and How to Fix It Automatically

Problem-Solution: Reducing Build Times from 45 Minutes to 8 Minutes

The Hidden Cost of Manual CI Debugging: A Data-Driven Analysis

How We Structured Our Docs to Answer the Questions Engineers Actually Ask

Own the Autonomous CI Resolution Conversation

Capture 100% of currently-missed visibility for 'Autonomous CI Failure Resolution' and 'Flaky Test Management' queries by developing dedicated landing pages and case studies. These assets will be optimized for LLM discovery and supported by social campaigns showcasing real customer wins and specific metrics that establish Mendral as the category leader.

We Fixed 847 Flaky Tests in One Quarter—Here's What We Learned

Flaky Test Management: Why Detection Alone Isn't Enough

Case Study: How One Team Eliminated 94% of CI-Related Pager Alerts

The True Cost of a Flaky Test Suite: Calculating Your Hidden Debt

Autonomous CI Resolution vs. Traditional Debugging: A Side-by-Side Comparison

Capture Engineering Director Procurement Visibility

Address the 0% Engineering Director persona visibility by creating high-level strategic content focused on ROI, dev-tooling consolidation, and business outcomes. This content will be structured for LLM citation during procurement research, with LinkedIn campaigns targeting decision-makers using concrete metrics and executive-focused messaging.

The ROI of Consolidating Your CI/CD Toolchain: A Finance-Ready Framework

What Engineering Directors Get Wrong About DevOps Tool Sprawl

How to Calculate the True Cost of CI Failures for Your Board

From 12 Tools to 3: One Director's Dev-Tooling Consolidation Playbook

Why Your Best Engineers Are Leaving: The Hidden Impact of CI Toil

Execute OpenAI SearchGPT Visibility Sprint

Raise the current 9% ChatGPT mention rate and improve average position from 26 to competitive levels through a focused technical SEO initiative. This includes optimizing web presence for OpenAI's browsing and indexing patterns, creating content that matches ChatGPT query patterns, and building social proof signals that OpenAI's systems prioritize.

How We Improved Our AI Search Visibility by 300% in 90 Days

The Technical SEO Checklist for Getting Cited by AI Assistants

What ChatGPT Gets Wrong About CI/CD Tools (And How to Fix It)

Building for AI Discovery: Lessons from the Docker Playbook

Why Your Competitors Show Up in ChatGPT and You Don't

Content Engineering

Recommended Actions

Optimize technical documentation and blogs for AI Overviews (SGE) by utilizing structured schema and clear, problem-solution header formats.

Mendral currently has 0% visibility in AI Overviews, which is the primary discovery engine for developers seeking immediate answers to CI/CD pain points.

Impact: High

Develop targeted landing pages and case studies specifically addressing 'Autonomous CI Failure Resolution' and 'Flaky Test Management'.

The brand is currently missing from every query related to these core value propositions, allowing competitors like Datadog to capture 100% of the share of voice.

Impact: High

Create high-level strategic content aimed at 'Engineering Directors' focusing on the ROI of dev-tooling consolidation.

With 0% visibility for the Engineering Director persona, Mendral is being excluded from the procurement-level research phase conducted via LLMs.

Impact: Medium

Execute a technical SEO sprint focused on OpenAI’s SearchGPT and ChatGPT-4o indexing to raise the current 9% mention rate.

ChatGPT's average position of 26.0 is significantly lower than Gemini (7.0), suggesting Mendral's web presence is not being prioritized by OpenAI's current training or browsing data.

Impact: Medium

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Backing

Investors

Y Combinator

Data generated by Pendium.ai AI visibility scanning. Last scanned February 27, 2026.

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