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

Get a demo

MatX

Visibility10

Vibe88

Businesses/Semiconductor / AI Hardware/MatX

AI Visibility & Sentiment

MatX

MatX is a semiconductor company building high-throughput AI chips specifically optimized for large language models. Their flagship MatX One chip delivers industry-leading performance for training and inference workloads at frontier AI labs, combining the efficiency of SRAM-first designs with HBM support for long-context applications.

Active Monitoring

matx.com

Semiconductor / AI Hardware Startups

AI Visibility Score

10/100

Invisible

Sentiment Score

88/100

Score by Priority

How often this business is recommended to users across different types of conversations — from direct product queries to broader open-ended conversations where AI could recommend this company's products and services

core

adjacent

AI Perception

Key Takeaways

How AI platforms collectively perceive and describe MatX today.

MatX is currently a ghost in the machine for high-stakes infrastructure decisions, remaining virtually non-existent in the critical conversations where enterprise architects design next-gen compute clusters. While the brand has found a niche foothold with startup CTOs, it is being systemically excluded from the 'Scaling Frontier AI Training' narrative dominated by NVIDIA and the CUDA ecosystem.

Working in your favor

Emerging resonance with the High-Growth AI Startup CTO persona, achieving a 21% mention rate

Strong performance in AI Overviews for brand-specific vibe checks, securing the #1 position

Consistently positive sentiment across ChatGPT and Claude when the brand is successfully surfaced

Gaps to close

Total absence from 'Scaling Frontier AI Training' and 'Direct Hardware Programming' query results

Zero visibility within the Google Gemini platform across all tested industry queries

Complete lack of penetration with Enterprise AI Procurement Directors, a critical decision-making persona

Opportunities

Pivot content strategy to target 'Direct Hardware Programming' to position MatX as the primary alternative to CUDA

Leverage the positive sentiment in ChatGPT to bridge the gap from startup interest to enterprise-grade infrastructure discussions

Aggressively optimize technical documentation for Gemini indexing to match the brand's performance in AI Overviews

Highest-Impact Actions

Produce deep-dive technical documentation on custom kernel optimization and direct hardware programming.

MatX is currently invisible in technical architecture queries where competitors like CUDA and ROCm are default answers; capturing this 'under-the-hood' search intent is vital for credibility.

Execute a Gemini-specific data seeding strategy focused on foundational compute cluster scaling.

A 0% mention rate on Gemini represents a critical failure in visibility that can be corrected by aligning web assets with Google's LLM training preferences.

Develop an 'Enterprise Readiness' content pillar specifically for Procurement Directors.

The 0% visibility with procurement personas prevents MatX from moving beyond the experimentation phase and into large-scale cluster contracts.

Value Proposition

The MatX One chip delivers higher throughput than any announced product while matching the best latencies, specifically designed from first principles for LLM workloads with no compromises for legacy use cases.

Overview

Mission

To make the best chips physically possible for the large model needs of frontier labs.

Products & Services

MatX One AI chipHigh-performance LLM training infrastructureLLM inference acceleration hardwareScale-out interconnect for large clustersDirect hardware programming model

Current State

Visibility Landscape

A high-level view of how MatX performs across AI platforms, broken down by strategic priority level — from core brand queries to growth opportunities.

	ChatGPT	Claude	Gemini	AI Overviews
Reputation1q Brand recognition & direct queries	70	70	97	97
“What do you know about MatX? What do they do and what's their reputation?”	Yes	Yes	#1	#1
Core5q Product/service category queries	23	17	0	26
“how do i build a massive compute cluster for training a foundation model from scratch, what hardware should i use”	—	No	No	No
“how can i get the lowest possible latency for real-time LLM inference for a production app”	#24	No	No	No
“are there any AI chips that allow direct hardware programming for custom transformer kernels”	No	No	No	No
“what's the best hardware for scaling LLM training beyond 10000 nodes right now, give me specific brands”	No	No	No	No
“find me high-throughput AI chips optimized for LLMs that aren't just standard GPUs”	—	#9	No	#6
Growth Areas1q Adjacent, aspirational & visionary	0	0	0	0
“who are the most trusted AI semiconductor companies for frontier labs right now”	No	No	No	No

“What do you know about MatX? What do they do and what's their reputation?”

Yes

“how do i build a massive compute cluster for training a foundation model from scratch, what hardware should i use”

—

“how can i get the lowest possible latency for real-time LLM inference for a production app”

#24

“are there any AI chips that allow direct hardware programming for custom transformer kernels”

“what's the best hardware for scaling LLM training beyond 10000 nodes right now, give me specific brands”

“find me high-throughput AI chips optimized for LLMs that aren't just standard GPUs”

—

“who are the most trusted AI semiconductor companies for frontier labs right now”

Competitive Landscape

NVIDIA

34 mentions

H100

26 mentions

CUDA

23 mentions

PyTorch

21 mentions

InfiniBand

20 mentions

ROCm

19 mentions

NVLink

18 mentions

H200

17 mentions

Cerebras

16 mentions

Blackwell

16 mentions

MatX

5 mentions

Analysis

Insights & Recommended Actions

What's working, what's not, and specific steps to improve MatX's AI visibility.

Key Findings

Strength

Emerging resonance with the High-Growth AI Startup CTO persona, achieving a 21% mention rate

Strength

Strong performance in AI Overviews for brand-specific vibe checks, securing the #1 position

Strength

Consistently positive sentiment across ChatGPT and Claude when the brand is successfully surfaced

Recommended Actions

Produce deep-dive technical documentation on custom kernel optimization and direct hardware programming.

MatX is currently invisible in technical architecture queries where competitors like CUDA and ROCm are default answers; capturing this 'under-the-hood' search intent is vital for credibility.

Execute a Gemini-specific data seeding strategy focused on foundational compute cluster scaling.

A 0% mention rate on Gemini represents a critical failure in visibility that can be corrected by aligning web assets with Google's LLM training preferences.

Develop an 'Enterprise Readiness' content pillar specifically for Procurement Directors.

The 0% visibility with procurement personas prevents MatX from moving beyond the experimentation phase and into large-scale cluster contracts.

Content Engineering

Content Ideas

Content designed to help AI agents learn about your category and recommend your brand.

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

Scaling Frontier AI Training(3 queries)

“how do i build a massive compute cluster for training a foundation model from scratch, what hardware should i use”

0/3 platforms mentioned

Core

Claude

1.NVIDIA

2.NVIDIA H100

3.NVIDIA A100

4.NVIDIA H200

5.TPU v5e

+28 more

Gemini

1.NVIDIA H100

2.NVIDIA Blackwell

3.B200

4.GB200

5.AMD Instinct MI300X

+40 more

AI Overviews

1.GreenNode

2.Runpod

3.NVIDIA B200

4.Blackwell

5.AMD Instinct MI300X

+12 more

“what's the best hardware for scaling LLM training beyond 10000 nodes right now, give me specific brands”

0/4 platforms mentioned

Core

The Frontier Lab Infrastructure Architect · Principal Infrastructure Engineer

ChatGPT

1.NVIDIA

2.HGX

3.H100

4.Blackwell

5.InfiniBand NDR

+51 more

Claude

1.NVIDIA

2.Blackwell

3.B200

4.B100

5.H100

+18 more

Gemini

1.NVIDIA Blackwell GB200 NVL72

2.NVLink Switch System

3.InfiniBand

4.Quantum-X800 InfiniBand

5.H100

+12 more

AI Overviews

1.NVIDIA

2.AMD

3.IntuitionLabs

4.Supermicro

5.StorageReview.com

+32 more

“find me high-throughput AI chips optimized for LLMs that aren't just standard GPUs”

1/3 platforms mentioned

Core

The Frontier Lab Infrastructure Architect · Principal Infrastructure Engineer

Claude

1.Cerebras WSE-3

2.H100

3.Graphcore IPU (Mk2)

4.CUDA

5.SambaNova SN40L

+8 more

Gemini

1.Groq

2.LPU

3.CUDA

4.GroqNode

5.Blackwell

+19 more

AI Overviews

1.Groq LPU

2.SambaNova SN50 RDU

3.SambaNova

4.Cerebras WSE-3

5.Google TPU v7

7.MatX One

+2 more

Source Intelligence

Citations

The sources AI platforms cite when recommending this brand. Pendium reverse-engineers what's already proven to be catnip to AI agents, then engineers content that fills gaps and helps agents do their job — which means more citations for you.

How to Design a GPU Cluster for AI Training - The Deep ...

youtube.com

Video1 ref

Best GPU for AI training (2026 guide) - Runpod

runpod.io

MatX

Key Takeaways

Visibility Landscape

Insights & Recommended Actions

Content Ideas

Sample Conversations

Citations

Brand Voice & Style

Investors

Engineer content that makes AI agents recommend you

Start gettingrecommended by AI.

Frequently asked questions

MatX

Key Takeaways

Visibility Landscape

Insights & Recommended Actions

Content Ideas

Sample Conversations

Citations

Brand Voice & Style

Investors

Engineer content that makes AI agents recommend you

Start gettingrecommended by AI.

Frequently asked questions

Start getting
recommended by AI.

Start getting
recommended by AI.