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.

Roadmap Pricing

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Extropic

Visibility28

Vibe91

Businesses/Semiconductor / Artificial Intelligence Hardware/Extropic

AI Visibility & Sentiment

Extropic

Extropic is a pioneering AI hardware company that utilizes thermodynamic computing to perform probabilistic calculations. By leveraging natural entropy, their technology offers massive energy efficiency improvements over traditional digital processors for generative AI workloads.

Active Monitoring

extropic.ai

Semiconductor / Artificial Intelligence Hardware Startups

AI Visibility Score

28/100

Low

Sentiment Score

91/100

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

aspirational

visionary

AI Perception

Key Takeaways

How AI platforms collectively perceive and describe Extropic today.

Extropic currently occupies a niche position in the AI hardware landscape, relying heavily on Gemini as its primary digital lighthouse while remaining largely invisible in broader research and infrastructure discourse. While the brand maintains high authority for direct identity queries, it fails to translate that recognition into the high-value 'hardware alternative' conversations that drive industry adoption.

Working in your favor

High recognition and brand authority on Gemini across both general inquiries and specialized compute hardware comparisons.

Effective brand narrative control on direct queries, achieving top-tier placement across all analyzed platforms when users specifically look for Extropic.

Successful alignment with Generative AI researchers, representing the strongest audience persona for the brand's current technical positioning.

Gaps to close

Total absence from critical 'high-efficiency hardware' and 'next-gen provider' search results on platforms like ChatGPT and AI Overviews.

Minimal penetration into the 'Chief Infrastructure Architect' persona, missing the gatekeepers who drive enterprise procurement.

Failure to capture traffic in adjacent software stack categories, particularly regarding thermodynamic modeling and energy-efficient optimization tools.

Opportunities

Capitalizing on the successful visibility in hardware comparison queries to expand presence into AI Overviews for broader discovery.

Establishing technical thought leadership in energy-efficient compute, bridging the gap between hardware hardware and software stack utility.

Actively targeting the infrastructure architect persona through content that demonstrates architectural maturity and enterprise scalability.

Highest-Impact Actions

Develop content specifically mapping Extropic’s hardware performance against established incumbents like NVIDIA and Cerebras.

Data shows users frequently search for alternatives to current market leaders; currently, Extropic is absent from these high-intent discovery phases.

Optimize technical documentation and whitepapers for AI Overviews and ChatGPT indexing.

Extropic relies too heavily on Gemini; diversifying across platforms is critical to building a robust search presence that isn't dependent on a single model's algorithm.

Publish targeted use-case studies focusing on thermodynamic modeling and energy efficiency in AI research.

There is a clear gap in the software/research space; content addressing these specific pain points will improve visibility with the under-served Generative AI researcher and architect segments.

Value Proposition

The company treats electrical noise as a computational asset rather than a hindrance, enabling the execution of generative AI sampling and denoising tasks with up to 10,000x greater energy efficiency than traditional GPUs.

Overview

Mission

To forge the ultimate physics-based computer that harnesses the natural entropy and fluctuations inherent in matter, redefining AI computation in ways that maximize efficiency in space, time, and energy.

Products & Services

Z1 ProcessorXTR-0 Development Platformthrml Python LibraryDenoising Thermodynamic Model (DTM)

Current State

Visibility Landscape

A high-level view of how Extropic 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	97	97	97	—
“What do you know about Extropic? What do they do and what's their reputation?”	#1	#1	#1	—
Core5q Product/service category queries	14	55	91	29
“what are the best hardware alternatives to gpus for running generative ai and denoising models efficiently”	No	No	#1	No
“compare specialized chips like z1 processor and other neuromorphic or thermodynamic compute platforms for ai workloads”	#15	#1	#1	—
“what python libraries should i use for denoising and thermodynamic ai modeling”	No	#1	#8	#8
“what are the most reliable companies currently building next-gen semiconductor chips for ai”	No	No	#3	—
“who are the main competitors to nvidia and cerebras for low-power ai inference”	No	No	#2	No
Growth Areas4q Adjacent, aspirational & visionary	0	18	74	44
“recommend high-performance hardware development platforms for testing probabilistic computing models”	No	No	#1	#3
“what are the best tools for optimizing energy consumption in large-scale generative ai pipelines”	No	#16	#1	No
“recommend advanced computing libraries for research organizations focused on physics-based ai”	No	No	No	No
“how do i evaluate the maturity of startups in the ai hardware space for my data center”	No	No	#7	—

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

—

“what are the best hardware alternatives to gpus for running generative ai and denoising models efficiently”

“compare specialized chips like z1 processor and other neuromorphic or thermodynamic compute platforms for ai workloads”

#15

—

“what python libraries should i use for denoising and thermodynamic ai modeling”

“what are the most reliable companies currently building next-gen semiconductor chips for ai”

—

“who are the main competitors to nvidia and cerebras for low-power ai inference”

“recommend high-performance hardware development platforms for testing probabilistic computing models”

“what are the best tools for optimizing energy consumption in large-scale generative ai pipelines”

#16

“recommend advanced computing libraries for research organizations focused on physics-based ai”

“how do i evaluate the maturity of startups in the ai hardware space for my data center”

—

Competitive Landscape

PyTorch

46 mentions

Groq

34 mentions

Cerebras

31 mentions

JAX

30 mentions

TensorFlow

27 mentions

NVIDIA

27 mentions

TSMC

27 mentions

Extropic

24 mentions

DeepXDE

20 mentions

Samsung

17 mentions

Tenstorrent

16 mentions

Analysis

Insights & Recommended Actions

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

Key Findings

Strength

High recognition and brand authority on Gemini across both general inquiries and specialized compute hardware comparisons.

Strength

Effective brand narrative control on direct queries, achieving top-tier placement across all analyzed platforms when users specifically look for Extropic.

Strength

Successful alignment with Generative AI researchers, representing the strongest audience persona for the brand's current technical positioning.

Recommended Actions

Develop content specifically mapping Extropic’s hardware performance against established incumbents like NVIDIA and Cerebras.

Data shows users frequently search for alternatives to current market leaders; currently, Extropic is absent from these high-intent discovery phases.

Optimize technical documentation and whitepapers for AI Overviews and ChatGPT indexing.

Extropic relies too heavily on Gemini; diversifying across platforms is critical to building a robust search presence that isn't dependent on a single model's algorithm.

Publish targeted use-case studies focusing on thermodynamic modeling and energy efficiency in AI research.

There is a clear gap in the software/research space; content addressing these specific pain points will improve visibility with the under-served Generative AI researcher and architect segments.

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

High Efficiency AI Compute Hardware Selection(3 queries)

“what are the best hardware alternatives to gpus for running generative ai and denoising models efficiently”

0/4 platforms mentioned

Core

ChatGPT

1.TensorFlow

2.JAX

3.Google Cloud

4.AWS (Trainium, Inferentia2)

5.Cerebras (WSE-3)

+11 more

Claude

1.TensorFlow

2.Qualcomm (Snapdragon)

3.MediaTek (Dimensity)

4.Intel (Agilex, Habana Gaudi3, oneAPI)

5.AMD (Versal, Instinct, ROCm)

+9 more

Gemini

1.Groq (Tensor Streaming Processor)

2.Llama 3

3.NVIDIA (H100)

4.Tenstorrent (Wormhole, Blackhole)

5.Cerebras (CS-3, Wafer-Scale Engine)

+4 more

AI Overviews

1.Groq (Groq 3)

2.Stable Diffusion

3.Google Cloud Platform

4.NVIDIA (H100)

“compare specialized chips like z1 processor and other neuromorphic or thermodynamic compute platforms for ai workloads”

2/3 platforms mentioned

Core

ChatGPT

1.AMD (Ryzen Z1, Zen 4, RDNA 3)

2.ASUS (ROG Ally)

3.Tesla (Dojo, D1)

4.IBM (Telum, z17, Telum II)

5.SpiNNaker

+8 more

Claude

1.Extropic AI (Z1)

2.Intel (Loihi 2)

3.IBM (NorthPole)

4.BrainScaleS-2

5.Heidelberg University

+10 more

Gemini

1.Extropic (Z1 processor, XTR-0, THRML)

2.Stable Diffusion

3.PyTorch

4.TensorFlow

“recommend high-performance hardware development platforms for testing probabilistic computing models”

0/4 platforms mentioned

Adjacent

ChatGPT

1.NVIDIA (Hopper, H100, Transformer Engine, DGX, HGX)

2.xAI

3.CUDA

4.cuDNN

5.NCCL

+16 more

Claude

1.NVIDIA

2.AMD (Vitis AI)

3.JAX

4.PyTorch

5.NumPyro

+14 more

Gemini

1.Intel (Loihi 2, Hala Point, Agilex 7, oneAPI)

2.IBM (NorthPole)

3.Purdue-P

4.AMD (Xilinx, Versal AI Core, Alveo U250, Alveo U280)

5.NVIDIA (H100, H200, Grace Hopper)

+2 more

AI Overviews

1.NVIDIA

2.CUDA

3.AMD (Xilinx)

4.Intel

5.Achronix

+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.

TPUs vs GPUs vs ASICs: AI Hardware Guide 2025 | AI Blog | HowAIWorks.ai

howaiworks.ai

Extropic

Key Takeaways

Visibility Landscape

Insights & Recommended Actions

Sample Conversations

Citations

Brand Voice & Style

Investors

Engineer content that makes AI agents recommend you

Start gettingrecommended by AI.

Frequently asked questions

Extropic

Key Takeaways

Visibility Landscape

Insights & Recommended Actions

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.