What does "AI visibility" mean for my business?

When someone asks ChatGPT, Claude, or Gemini "what is the best..." or "where can I find...", AI gives specific recommendations. AI visibility is a measure of how often — and how positively — these AI platforms mention your business. It's the new version of being on the first page of Google, except now there are no pages — just one answer.

Which AI platforms do you monitor?

Pendium monitors ChatGPT, Claude, Gemini, Grok, Perplexity, DeepSeek, and Google AI Overviews — seven major AI platforms that consumers use to research local services. We run real queries that your customers actually ask and analyze the responses for mentions of your business, competitors, and industry topics.

How does Pendium improve my visibility?

Three ways. First, we identify the exact queries and topics where you're invisible. Second, we generate AI-optimized content — articles, guides, social posts — designed to help AI agents understand your business and recommend your services to the right people. Third, we continuously monitor to track improvement and find new opportunities. Most clients see measurable improvement within 60 days.

How long until I see results?

You'll get your first visibility report within minutes of signing up. Actual visibility improvement varies, but our clients typically see a 47% average improvement within 60 days. Some see results faster — it depends on your current online presence and how competitive your local market is.

Do I need to be technical to use this?

Not at all. Enter your website URL and Pendium handles everything: scanning AI platforms, analyzing your visibility, generating content, and tracking improvement. The dashboard is designed for business owners, not engineers. If you can check your email, you can use Pendium.

What makes this different from SEO?

Traditional SEO optimizes for Google's search rankings — blue links on a results page. AI visibility is different: AI doesn't show links, it gives direct answers. Even if you rank #1 on Google, ChatGPT might recommend a competitor. Pendium optimizes for the new paradigm — making sure AI platforms know about, trust, and recommend your business.

Pricing

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Moda

Visibility0

Vibe50

Businesses/Software/Moda

AI Visibility & Sentiment

Moda

Moda is an AI agent monitoring platform that automatically detects behavioral failures in LLM applications that traditional logs miss. It catches issues like agent forgetfulness, tool misuse, and user frustration in real-time, helping teams identify and fix silent failures before users complain.

Active Monitoring

modaflows.com

Software YC25-26

AI Visibility Score

0/100

Invisible

Sentiment Score

50/100

AI Perception

Summary

Moda currently suffers from a total visibility blackout across the LLM observability landscape, ceding the entire conversation to established players like LangSmith and Datadog. This complete absence during critical troubleshooting queries regarding AI agent hallucinations and real-time alerting represents a significant missed opportunity to capture the market's most urgent pain points.

Value Proposition

Catch AI agent behavioral failures that don't show up in stack traces or error logs—automatically detect when agents forget context, misuse tools, give lazy responses, or frustrate users, with no configuration needed.

Overview

Mission

Stop reading logs. Start seeing failures.

Products & Services

AI agent behavioral monitoringCustom signal detection for LLM failuresReal-time alerting via Slack, email, and webhooksConversation analytics dashboardPython and Node.js SDKs for OpenAI, Anthropic, and AWS Bedrock

Agent Breakdown

AI Platforms

How often do different AI platforms reference Moda?

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Conversation Analysis

Topics

What conversations is Moda included in — or excluded from?

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Buyer Personas

Personas

Who does each AI platform recommend Moda 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

Troubleshooting AI Agent Failures(2 queries)

“my ai agent is hallucinating and getting stuck in loops, how can i track when this happens in production?”

0/4 platforms mentioned

ChatGPT

1.S3

2.GS

3.BigQuery

4.ClickHouse

5.Snowflake

+24 more

Claude

1.Weights & Biases

2.LangSmith

3.LangChain

4.Arize

5.Prometheus

+1 more

Gemini

1.Datadog

2.LangSmith

3.LangChain

4.Arize Phoenix

5.Helicone

+10 more

AI Overviews

1.Maxim AI

2.ISHIR

3.LangGraph

4.CrewAI

“how to detect when a chatbot is frustrating users or misusing tools before they actually report it”

0/4 platforms mentioned

ChatGPT

1.Kafka

2.Prometheus

3.Alertmanager

4.Flink

5.ksqlDB

+20 more

Claude

1.OpenTelemetry

2.Datadog

3.Arize AI

4.Langsmith

5.Python

+4 more

Gemini

1.OpenTelemetry

2.ClickHouse

3.Snowflake

4.Pydantic

5.Llama-3-8B

+8 more

AI Overviews

1.MonkeyLearn

2.Google Natural Language API

3.Freshworks

Evaluating LLM Observability Platforms(1 query)

“best llm observability and monitoring tools for 2026, looking for something that catches behavioral issues specifically”

0/4 platforms mentioned

ChatGPT

1.Arize AI

2.LangSmith

3.LangChain

4.Robust Intelligence

5.Fiddler AI

+20 more

Claude

1.Arize AI

2.Langfuse

3.Humanloop

4.WhyLabs

5.DataRobot AI Cloud

+1 more

Gemini

1.Arize Phoenix

2.Arize AI

3.LangSmith

4.LangChain

5.Giskard

+7 more

AI Overviews

1.Maxim AI

2.Galileo

3.Openlayer

4.Arize Phoenix

5.Arize AX

+1 more

AI Infrastructure & Alerting Setup(1 query)

“setup real time slack alerts for when my openai agent fails a task or gives a lazy response”

0/4 platforms mentioned

ChatGPT

1.Slack

2.Sentry

3.Datadog

4.Slack Bolt

5.Flask

+6 more

Claude

1.Slack

2.Python

3.LangChain

4.LangSmith

5.Sentry

+3 more

Gemini

1.Slack

2.LangSmith

3.LangChain

4.Helicone

5.Portkey

+7 more

AI Overviews

1.Slack

2.Datadog LLM Observability

3.n8n

4.Neubird Hawkeye

5.Galileo

AI Product Analytics & User Retention(1 query)

“how to build a dashboard to track ai agent performance and user frustration metrics”

0/4 platforms mentioned

ChatGPT

1.Kafka

2.AWS Kinesis

3.Google PubSub

4.ksqlDB

5.Apache Flink

+30 more

Claude

1.Hugging Face

2.MonkeyLearn

3.Sentry

4.InfluxDB

5.Prometheus

+16 more

Gemini

1.LangSmith

2.LangChain

3.Arize Phoenix

4.Helicone

5.PostHog

+11 more

AI Overviews

1.Rasa

2.UptimeRobot

3.Braintrust

4.Langfuse

5.Arize Phoenix

+3 more

Analysis

Key Insights

What AI visibility analysis reveals about this brand

Strength

The competitive landscape is clearly defined, with LangSmith and LangChain setting the benchmark for the LLM observability discourse that Moda must disrupt.

Gap

Total lack of presence in high-intent troubleshooting searches such as 'my ai agent is hallucinating and getting stuck in loops.'

Gap

Zero recognition from critical technical personas, specifically the Speed-Obsessed Startup CTO and the Scaled AI Infrastructure Lead.

Gap

Complete failure of the 'brand vibe check,' indicating that AI models lack the training data to even define what Moda is or does.

Gap

Failure to appear in queries involving integration-heavy workflows like real-time Slack alerting for agent failures.

Opportunity

Claim the 'Troubleshooting AI Agent Failures' niche by creating technical content that solves specific hallucination and loop issues.

Opportunity

Differentiate from generalists like Datadog and Sentry by focusing on GenAI-specific observability metrics.

Opportunity

Target the UX-Focused GenAI Product Manager by producing documentation on dashboarding for AI user retention.

Technical Health

Site Health for AI Visibility

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

73/100

6 passed 3 warnings 5 issues

Audited 2/27/2026

Crawlability79

Can AI bots find your pages?

Technical80

SSL, mobile, doctype basics

On-Page SEO58

Titles, descriptions, headings

Content Quality55

Word count, depth, freshness

Schema Markup85

Structured data for AI comprehension

Social & OG77

Open Graph, Twitter cards

AI Readability85

How well AI can parse your content

Critical Issues

Page returns a 404 error

Fix the underlying issue causing the error. 404s should be redirected or the link removed.

Page has no title tag

Add a <title> tag describing the page content (50-60 characters).

Page has no meta description

Add a <meta name="description"> tag summarizing the page (150-160 characters).

Page has no H1 heading

Add a single H1 tag as the main page heading.

Content is too thin

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

Warnings

No robots.txt file found

Create a robots.txt file at your domain root. Optional but recommended.

Few headings on page

Add more H2 and H3 headings to organize content into sections.

Few internal links on this page

Add more internal links to related pages on your site.

Missing Open Graph tags for social sharing

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

LCP data not available

Ensure the page loads with browser rendering enabled.

+ 1 more warnings

Want a full technical audit with AI-specific recommendations?

Run a free visibility scan

Brand Identity

Brand Voice & Style

How AI perceives Moda's communication style and personality

Moda communicates with a direct, technically confident voice that speaks developer-to-developer. The tone is sharp and punchy, using concrete examples and real failure scenarios rather than abstract promises. There's an underlying urgency—your agents are failing right now and you don't know it—balanced with calm expertise. The brand avoids corporate jargon, preferring plain language that cuts to the problem and solution quickly.

Core Tone Traits

Direct & Punchy

Short, impactful statements that cut through noise. 'No stack trace. No error log. Still broken.'

Technically Credible

Speaks with developer fluency, using real code examples and specific failure scenarios

Urgently Helpful

Creates awareness of hidden problems while immediately offering solutions

Plain-Spoken

Avoids marketing fluff in favor of clear, honest language about what the product does

Competitive Landscape

Related Ecosystem

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

LangSmith28 mentions

LangChain20 mentions

Datadog14 mentions

Slack14 mentions

Grafana13 mentions

Arize AI13 mentions

Sentry12 mentions

OpenTelemetry12 mentions

Prometheus11 mentions

Helicone11 mentions

Moda0 mentions

Source Intelligence

Citations

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

Top 5 Tools to Monitor and Detect Hallucinations in AI Agents

https://www.getmaxim.ai/articles/top-5-tools-to-monitor-and-detect-hallucinations-in-ai-agents/

Referenced in 1 query

Review

Measuring LLM Hallucinations: The Metrics That Actually Matter for ...

https://www.getmaxim.ai/articles/measuring-llm-hallucinations-the-metrics-that-actually-matter-for-reliable-ai-apps/

Referenced in 1 query

Review

Troubleshooting agent loops: patterns, alerts, safe fallbacks ...

https://www.getmaxim.ai/articles/troubleshooting-agent-loops-patterns-alerts-safe-fallbacks-and-tool-governance-using-maxim-ai/

Referenced in 1 query

Review

5 Best Hallucination Detection Tools for LLM Applications

https://galileo.ai/blog/best-hallucination-detection-tools-llm

Referenced in 1 query

Review

LLM Hallucinations in Production: Monitoring Strategies That ...

https://www.getmaxim.ai/articles/llm-hallucinations-in-production-monitoring-strategies-that-actually-work/

Referenced in 1 query

Review

Context Drift in AI Agents: Why Your Agent Loops ... - Tacnode

https://tacnode.io/post/your-ai-agents-are-spinning-their-wheels

Referenced in 1 query

Review

Top 5 tools to detect hallucination in 2025 - Maxim AI

https://www.getmaxim.ai/articles/top-5-tools-to-detect-hallucination-in-2025/

Referenced in 1 query

Review

5 Ways to Detect AI Agent Hallucinations - DEV Community

https://dev.to/kamya_shah_e69d5dd78f831c/5-ways-to-detect-ai-agent-hallucinations-3hb8

Referenced in 1 query

Review

How to Build Reliable AI Agent Evaluation Loops (Without ...

https://medium.com/@joshSzep/how-to-build-reliable-ai-agent-evaluation-loops-without-guesswork-2eef63b299d0

Referenced in 1 query

Review

Our Agent Had A 4 Minute Loop. Here’s How We Fixed It. - Medium

https://medium.com/data-science-collective/our-agent-had-a-4-minute-loop-heres-how-we-fixed-it-40a8142ef1a9

Referenced in 1 query

Review

Top Tools and Plugins to Detect AI Hallucinations in Real-Time - ISHIR

https://www.ishir.com/blog/183214/top-tools-and-plugins-to-detect-ai-hallucinations-in-real-time.htm

Referenced in 1 query

Review

Agentic AI: The Agent Loop & Tools for Building ... - You.com

https://you.com/resources/the-agent-loop-how-ai-agents-actually-work-and-how-to-build-one

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 Moda's resources to help users.

Establish Technical Authority on Agent Debugging

Address the critical visibility gap where Moda is invisible for high-pain debugging queries. Create and distribute a comprehensive technical guide on debugging agent hallucination loops, optimized for LLM ingestion with structured data and clear problem-solution formatting. Amplify through developer communities and social channels to build backlinks and citations that AI models will reference.

The 5 most common hallucination loop patterns we see in production LLM agents and how to break them

Why your agent keeps forgetting mid-conversation: a technical deep-dive into context window failures

Real debugging session: tracing a hallucination loop from user complaint to root cause fix

The hidden cost of agent hallucination loops—what silent failures are costing your team right now

Checklist: 10 signs your LLM agent is stuck in a hallucination loop

Launch Digital PR Brand Authority Campaign

Fix the failed brand vibe check by executing a targeted digital PR campaign that defines Moda as the go-to LLM observability platform. Secure mentions in high-authority tech publications, developer blogs, and industry databases that AI models reference when making recommendations. Social media will amplify PR wins and reinforce consistent messaging about Moda's core identity.

What is LLM observability and why traditional APM tools completely miss behavioral failures

The difference between error logs and behavioral monitoring—why your agents fail silently

How we caught 47 silent agent failures in one week that never hit any error dashboard

Why engineering teams are adding behavioral monitoring to their AI stack in 2026

Moda explained: catching the agent failures that don't throw exceptions

Position Moda in LLM Tooling Comparisons

Break into the consideration set for Startup CTOs searching for observability tools by creating a definitive 2026 LLM Observability Comparison whitepaper. Explicitly position Moda against LangSmith and Arize AI with honest feature comparisons. Distribute insights through social channels and developer forums to generate organic discussion and improve visibility in competitive queries.

Moda vs LangSmith vs Arize AI: which catches behavioral failures your logs miss

The 2026 LLM observability landscape—what's changed and what still doesn't work

Choosing an LLM monitoring tool: the questions most comparison guides don't ask

Why we built Moda differently than existing observability platforms

Feature breakdown: what to look for in an AI agent monitoring tool this year

Integrate Into Developer Infrastructure Ecosystem

Address the Slack and Grafana ecosystem gap by developing and documenting a native Slack integration for AI failure alerts. Create content showing how Moda fits into existing developer workflows and infrastructure setups that AI models frequently recommend. Social proof through integration announcements and workflow tutorials will help Moda appear in infrastructure recommendation queries.

Get Slack alerts when your AI agent frustrates users—before they complain

How to add behavioral failure alerts to your existing observability stack in 15 minutes

The modern AI monitoring workflow: from silent failure detection to Slack notification

Why your on-call rotation needs behavioral alerts, not just error alerts

Building an AI agent alerting pipeline that actually catches the failures that matter

Content Engineering

Recommended Actions

Publish a comprehensive technical guide on 'Debugging Agent Hallucination Loops' optimized for LLM ingestion.

This addresses the most frequent and high-pain query where Moda is currently invisible while competitors are gaining traction.

Impact: High

Execute a digital PR campaign to define the brand's core identity and use cases.

The brand vibe check failed completely; AI models need more high-authority mentions to associate Moda with LLM observability.

Impact: High

Develop and document a native Slack integration for AI failure alerts.

Query data shows Slack and Grafana are frequently mentioned in infrastructure setups, and Moda should be part of that ecosystem's recommendation engine.

Impact: Medium

Create a '2026 LLM Observability Comparison' whitepaper that explicitly positions Moda against LangSmith and Arize AI.

Directly targeting the 'best llm observability and monitoring tools' query will help Moda break into the consideration set for the Startup CTO persona.

Impact: Medium

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