Corelayer

Visibility6

Vibe75

AI Visibility & Sentiment

Corelayer

Corelayer is an AI-powered on-call engineering platform designed for financial services and fintech companies. It continuously monitors logs, data, and infrastructure for issues, using AI agents to automatically debug production problems and suggest fixes within minutes.

Active Monitoring

corelayer.com

Software YC25-26

AI Visibility Score

6/100

Invisible

Sentiment Score

75/100

AI Perception

Summary

Corelayer currently operates as a ghost in the AI recommendation landscape, failing to surface in high-stakes fintech and security queries where competitors like Datadog and PagerDuty dominate. While the brand has established a promising foothold with 'Burned-Out SRE' personas on Gemini and Claude, it remains completely invisible to the strategic decision-makers who control enterprise budgets.

Value Proposition

Reduce production support time by up to 70% with AI agents that automatically detect issues, identify root causes, and suggest fixes—all while maintaining enterprise-grade security with SOC 2 compliance and confidential compute.

Overview

Mission

To free engineers from the burden of production support so they can spend more time building valuable data products.

Products & Services

AI-powered production issue detection and monitoringAutomated root cause analysisAI-generated fix suggestions with PR creationMulti-platform integrations (Snowflake, AWS, GCP, Datadog, etc.)Confidential compute for sensitive data environments

Agent Breakdown

AI Platforms

How often do different AI platforms reference Corelayer?

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Conversation Analysis

Topics

What conversations is Corelayer included in — or excluded from?

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Buyer Personas

Personas

Who does each AI platform recommend Corelayer 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

Automating Production Incident Response(3 queries)

“how can i use AI to automate root cause analysis for my production logs”

0/4 platforms mentioned

ChatGPT

1.OpenTelemetry

2.Fluentd

3.Fluent Bit

4.Filebeat

5.Logstash

+59 more

Claude

1.ELK Stack

2.Elasticsearch

3.Logstash

4.Kibana

5.Python

+11 more

Gemini

1.Datadog

2.Watchdog

3.Dynatrace

4.Davis AI

5.ScienceLogic

+19 more

AI Overviews

1.ScienceLogic

2.LogicMonitor

3.Datadog Watchdog

4.Dynatrace Davis

5.New Relic Applied Intelligence

+6 more

“help me find tools that don't just alert but actually suggest code fixes and create PRs for infra issues”

0/3 platforms mentioned

Claude

1.GitHub Copilot

2.CodeQL

3.GitHub Enterprise

4.Datadog

5.Snyk

+10 more

Gemini

1.Firefly

2.Dazz

3.Snyk

4.Snyk Infrastructure as Code

5.Kubiya

+2 more

AI Overviews

1.Gomboc

2.Terraform

3.Pulumi

4.CloudFormation

5.Aikido Security

+8 more

“i'm tired of manual on-call, what are the best AI agents for production issue detection right now”

0/4 platforms mentioned

ChatGPT

1.Dynatrace

2.Davis AI

3.BigPanda

4.Moogsoft

5.Datadog

+16 more

Claude

1.PagerDuty

2.EventIntelligence

3.Datadog

4.Moogsoft Enterprise

5.Rundeck

+2 more

Gemini

1.Shoreline.io

2.AWS

3.Kubernetes

4.PagerDuty Savvy

5.PagerDuty

+9 more

AI Overviews

1.incident.io

2.Rootly

3.Jira

4.Xurrent IMR

5.Sera AI

+12 more

Secure Monitoring For Regulated Industries(1 query)

“best observability platforms for fintech companies that handle highly sensitive data”

0/4 platforms mentioned

ChatGPT

1.Splunk

2.Splunk Observability Cloud

3.Splunk Enterprise

4.Datadog

5.Dynatrace

+35 more

Claude

1.Datadog

2.New Relic

3.Elastic Stack

4.Elastic Cloud

5.Splunk

+1 more

Gemini

1.Splunk

2.Data Stream Processor

3.Splunk Cloud

4.Dynatrace

5.OneAgent

+25 more

AI Overviews

1.Splunk

2.Cisco

3.Dynatrace

4.Davis AI

5.Datadog

+6 more

Evaluating AI Powered Observability Tools(1 query)

“most trusted AI-powered observability and incident response platforms in 2026”

0/4 platforms mentioned

ChatGPT

1.Datadog

2.Datadog Watchdog

3.Dynatrace

4.Davis

5.Splunk

+20 more

Claude

1.Datadog

2.New Relic

3.Splunk

4.Splunk Cloud Platform

5.Elastic

+4 more

Gemini

1.Datadog

2.Bits AI

3.Dynatrace

4.Davis AI

5.New Relic

+20 more

AI Overviews

1.Dynatrace

2.Davis AI

3.Datadog

4.Bits AI

5.New Relic

+12 more

Analysis

Key Insights

What AI visibility analysis reveals about this brand

Strength

Achieved a 27% mention rate with the 'Burned-Out Senior SRE Lead' persona, suggesting the technical narrative resonates with practitioner-focused AI models.

Strength

Maintains a strong positive sentiment and a top-tier rank (#1) on Claude and AI Overviews for brand-specific 'vibe check' queries.

Strength

Surfaces for 'Automating Production Incident Response' on Gemini and Claude, showing foundational indexing for core technical capabilities.

Gap

Zero visibility for the 'Strategic Fintech CTO' persona across all tested queries, missing the most critical buyer demographic.

Gap

Complete absence from 'Secure Monitoring for Regulated Industries' results, ceding the entire fintech observability market to legacy competitors.

Gap

Extremely poor average positioning on ChatGPT (31.0), which effectively buries the brand behind dozens of alternatives in discovery sessions.

Opportunity

Leverage existing SRE resonance to bridge the gap into executive-level queries by emphasizing the 'Strategic' and 'Compliance' benefits of automated root cause analysis.

Opportunity

Target Gemini’s 17% mention rate by optimizing technical documentation for 'AI agents for on-call,' a high-intent category currently dominated by PagerDuty.

Opportunity

Improve ChatGPT visibility by seeding more authoritative third-party comparisons that highlight Corelayer alongside industry leaders like Dynatrace and New Relic.

Technical Health

Site Health for AI Visibility

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

89/100

15 passed 5 warnings

Audited 2/27/2026

Crawlability96

Can AI bots find your pages?

Technical96

SSL, mobile, doctype basics

On-Page SEO80

Titles, descriptions, headings

Content Quality87

Word count, depth, freshness

Schema Markup85

Structured data for AI comprehension

Social & OG82

Open Graph, Twitter cards

AI Readability60

How well AI can parse your content

Warnings

3 render-blocking resource(s) detected

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

Title is too short (28 characters)

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

Meta description is too short (30 characters)

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

H3 used without H2 — heading levels are skipped

Use headings in order (H1 → H2 → H3). Don't skip levels.

Missing Open Graph tags for social sharing

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

Want a full technical audit with AI-specific recommendations?

Run a free visibility scan

Brand Identity

Brand Voice & Style

How AI perceives Corelayer's communication style and personality

Corelayer communicates with technical precision and confidence, speaking directly to engineers who understand the pain of production debugging. The tone is professional yet approachable, avoiding corporate jargon while demonstrating deep domain expertise. They lead with concrete value propositions and quantifiable outcomes, backed by Y Combinator credibility. The voice balances technical authority with empathy for the engineer's daily struggles, making complex AI capabilities feel accessible and practical.

Core Tone Traits

Technical & Precise

Uses specific engineering terminology and concrete metrics without oversimplifying for technical audiences

Confident & Direct

Makes clear value claims backed by evidence, avoiding hedging language

Empathetic to Engineers

Acknowledges the real pain points of production support and on-call duties

Security-Conscious

Emphasizes compliance, data protection, and enterprise-grade security as core values

Competitive Landscape

Related Ecosystem

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

Datadog30 mentions

PagerDuty18 mentions

Splunk16 mentions

Dynatrace16 mentions

Elasticsearch12 mentions

Prometheus12 mentions

Davis AI12 mentions

New Relic11 mentions

Snyk11 mentions

Grafana10 mentions

Corelayer4 mentions

Source Intelligence

Citations

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

How AI Improves Root Cause Analysis Automation - Latenode

https://latenode.com/blog/workflow-automation-business-processes/business-process-automation-fundamentals/how-ai-improves-root-cause-analysis-automation

Referenced in 1 query

Review

How to Analyze Logs Using AI - LogicMonitor

https://www.logicmonitor.com/blog/how-to-analyze-logs-using-artificial-intelligence

Referenced in 1 query

Review

Manufacturing Root Cause Analysis with Causal AI - Databricks

https://www.databricks.com/blog/manufacturing-root-cause-analysis-causal-ai

Referenced in 1 query

Review

How AI Is Transforming Root Cause Analysis in Software and ...

https://reliability.com/resources/how-ai-is-transforming-root-cause-analysis-in-software-and-beyond/

Referenced in 1 query

Review

AI-Powered Root Cause in ITSM | EasyVista

https://www.easyvista.com/blog/ai-powered-root-cause-itsm-transforming-incident-resolution-enhancing-operational-efficiency/

Referenced in 1 query

Review

AI in Root Cause Analysis: How Emerging Tools Are ...

https://reliability.com/resources/ai-in-root-cause-analysis/

Referenced in 1 query

Review

Dynatrace AI-driven root cause and impact analysis

https://www.dynatrace.com/news/blog/build-trust-with-dynatrace-ai-driven-root-cause-and-impact-analysis/

Referenced in 1 query

Review

Top 8 AI-Powered Anomaly Detection Tools for Time Series Data

https://www.anodot.com/learning-center/top-8-ai-powered-anomaly-detection-tools-for-time-series-data/

Referenced in 1 query

Review

How AI Root Cause Analysis Improves Maintenance Decisions

https://llumin.com/blog/how-ai-root-cause-analysis-improves-maintenance-decisions/

Referenced in 1 query

Review

Automated Root Cause Analysis | ScienceLogic

https://sciencelogic.com/articles/automated-root-cause-analysis

Referenced in 1 query

Review

The Role of AI in Root Cause Analysis (RCA) - testRigor

https://testrigor.com/blog/the-role-of-ai-in-root-cause-analysis/

Referenced in 1 query

Review

Data Observability Tools: Top 10 Platforms to Evaluate in 2026

https://www.ovaledge.com/blog/data-observability-tools/

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 Corelayer's resources to help users.

Launch Fintech Observability Case Study Campaign

Address the 0% mention rate for fintech and secure monitoring queries by creating and publishing detailed case studies showcasing Corelayer's regulatory compliance capabilities. This content will be optimized for indexing by AI assistants, targeting CTO personas searching for compliant observability solutions. Social media will amplify these case studies through technical deep-dives and compliance-focused snippets that establish authority in the fintech monitoring space.

How a Series B Fintech Cut SOC 2 Audit Prep Time by 60% with Automated Log Monitoring

The Hidden Cost of Non-Compliant Observability Tools in Financial Services

5 Regulatory Requirements Your Monitoring Stack Probably Isn't Meeting

Why Traditional APM Tools Fail Fintech Security Audits—And What CTOs Should Demand Instead

Building a Compliance-First Observability Strategy for PCI-DSS Environments

Optimize Root Cause Analysis Content for Gemini

Capitalize on Gemini's existing 17% brand awareness by creating and optimizing technical documentation and blog content specifically targeting root cause analysis queries. This strategy focuses on improving ranking from #27 to top 10 by publishing detailed, structured content that Gemini's algorithms favor. Social media will drive engagement signals and backlinks to this technical content through engineer-focused discussions and debugging insights.

The 5-Minute Root Cause Analysis Framework Every On-Call Engineer Needs

Why Most Production Debugging Takes Hours Instead of Minutes

Root Cause Analysis Checklist: From Alert to Resolution in Under 10 Minutes

Common Root Cause Analysis Mistakes That Keep Engineers Up All Night

How AI-Powered Log Correlation Eliminates Manual Debugging Guesswork

Establish AI Agent Narrative Leadership

Counter competitors like PagerDuty and Davis AI by repositioning Corelayer's messaging around AI agents for incident response rather than basic alerting. This addresses the high-growth SRE search trend and captures mindshare in AI-powered operations conversations. Social media content will showcase autonomous debugging capabilities and differentiate Corelayer's agent-first approach through technical demonstrations and outcome-focused messaging.

Beyond Alerting: What True AI Agents Actually Do During Production Incidents

The Difference Between AI-Assisted and AI-Autonomous Incident Response

Why Your Current 'AI-Powered' Monitoring Tool Is Just Fancy Pattern Matching

How AI Agents Debug Production Issues While You Sleep

From Alert Fatigue to Autonomous Resolution: The AI Agent Evolution in SRE

Build Technical Authority in Financial Services DevOps

Create a comprehensive content footprint targeting financial services engineering leaders by publishing authoritative technical content across platforms that LLMs reference. This establishes Corelayer as the go-to voice for regulated industry observability, improving visibility across all AI assistants. Social media will position engineering team members as thought leaders through insights on secure infrastructure monitoring and compliant debugging practices.

What Bank CTOs Wish Their Engineering Teams Knew About Production Monitoring

Confidential Compute Explained: Why It Matters for Financial Services Debugging

The Real Cost of a 4-Hour Production Outage in Financial Services

How Regulated Industries Should Evaluate AI-Powered DevOps Tools

Security vs Speed: Why Financial Services Teams Shouldn't Have to Choose

Content Engineering