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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Inference

Visibility64

Vibe51

Businesses/Artificial Intelligence/Inference

AI Visibility & Sentiment

Inference

Inference provides custom, task-specific AI models that offer significantly higher performance, lower latency, and reduced costs compared to general-purpose frontier models. They partner with engineering teams to train, host, and optimize specialized AI solutions for various modalities.

Active Monitoring

inference.net

Artificial Intelligence

AI Visibility Score

64/100

Good

Sentiment Score

51/100

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 Inference today.

Inference has secured a strong foothold with technical leaders and enterprise strategists, establishing itself as a credible alternative to incumbent giants like OpenAI and Anthropic. While the brand performs well in high-intent conversations regarding cost reduction and scalable infrastructure, it currently misses critical opportunities to sway startup founders who are actively seeking specialized, budget-friendly AI solutions.

Working in your favor

High brand recognition among technical decision-makers and enterprise strategists.

Strong performance across major LLM-integrated platforms like ChatGPT, Claude, and Gemini.

Proven authority in 'high-intent' technical categories, specifically for LLM cost-reduction and infrastructure scaling queries.

Gaps to close

Weak visibility with cost-conscious startup founders, failing to capitalize on the 'budget-aware' search segment.

Inconsistent presence in custom model training discussions compared to infrastructure deployment topics.

Lack of competitive differentiation against hardware-focused giants like NVIDIA in broader ecosystem queries.

Opportunities

Leverage existing enterprise authority to create educational content specifically targeting cost-conscious startup founder personas.

Strengthen thought leadership in custom model training to capture the segment of users currently not connecting the brand to specialized tasks.

Amplify presence in AI Overviews to improve positioning relative to emerging competitors like Groq and Together AI.

Highest-Impact Actions

Develop and syndicate case studies tailored to the 'Cost-Focused Startup Founder' persona.

Current data shows a significant drop-off in visibility for this persona; directly addressing budget constraints with startup-specific use cases will fill this conversion gap.

Create content pillars explicitly linking Inference capabilities to custom model training workflows.

Inconsistent mentions in model specialization queries suggest a disconnect in how the market perceives Inference's utility beyond standard API deployment.

Optimize technical documentation and whitepapers for AI Overview search synthesis.

While general brand sentiment is neutral, improving the 'answerability' of Inference content will help capture higher placement in automated summary results against rivals like vLLM.

Value Proposition

Delivers frontier-level intelligence at a fraction of the cost, with up to 95% lower costs and 2-3x faster speeds than standard frontier models.

Overview

Products & Services

Custom Model TrainingServerless Inference APIBatch Inference APIDedicated InferenceOpen Source Models

Current State

Visibility Landscape

A high-level view of how Inference 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	70	70	70
“What do you know about Inference? What do they do and what's their reputation?”	#1	Yes	Yes	Yes
Core3q Product/service category queries	70	70	70	70
“our current LLM API bill is getting too high, how can we switch to something cheaper but still performant”	—	Yes	Yes	Yes
“what are the best ways to deploy open source models for a high-traffic app”	Yes	Yes	Yes	Yes
“how do i speed up our model inference time, we are currently using standard frontier models”	Yes	Yes	Yes	Yes
Growth Areas2q Adjacent, aspirational & visionary	70	70	70	70
“is it worth training a custom model for a specific task instead of prompting gpt-4”	Yes	Yes	Yes	Yes
“who are the most reliable alternatives to openai and anthropic for hosting models”	Yes	Yes	Yes	Yes

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

Yes

“our current LLM API bill is getting too high, how can we switch to something cheaper but still performant”

—

Yes

“what are the best ways to deploy open source models for a high-traffic app”

Yes

“how do i speed up our model inference time, we are currently using standard frontier models”

Yes

“is it worth training a custom model for a specific task instead of prompting gpt-4”

Yes

“who are the most reliable alternatives to openai and anthropic for hosting models”

Yes

Competitive Landscape

NVIDIA

17 mentions

GPT-4

16 mentions

vLLM

16 mentions

SiliconFlow

14 mentions

Groq

12 mentions

Together AI

12 mentions

Mistral

12 mentions

Hugging Face

12 mentions

Mistral AI

11 mentions

Llama

9 mentions

Inference

0 mentions

Analysis

Insights & Recommended Actions

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

Key Findings

Strength

High brand recognition among technical decision-makers and enterprise strategists.

Strength

Strong performance across major LLM-integrated platforms like ChatGPT, Claude, and Gemini.

Strength

Proven authority in 'high-intent' technical categories, specifically for LLM cost-reduction and infrastructure scaling queries.

Recommended Actions

Develop and syndicate case studies tailored to the 'Cost-Focused Startup Founder' persona.

Current data shows a significant drop-off in visibility for this persona; directly addressing budget constraints with startup-specific use cases will fill this conversion gap.

Create content pillars explicitly linking Inference capabilities to custom model training workflows.

Inconsistent mentions in model specialization queries suggest a disconnect in how the market perceives Inference's utility beyond standard API deployment.

Optimize technical documentation and whitepapers for AI Overview search synthesis.

While general brand sentiment is neutral, improving the 'answerability' of Inference content will help capture higher placement in automated summary results against rivals like vLLM.

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

Reducing AI Inference Costs And Latency(2 queries)

“our current LLM API bill is getting too high, how can we switch to something cheaper but still performant”

2/3 platforms mentioned

Core

Claude

1.DeepSeek

2.GPT-5

3.Mistral AI

4.SiliconFlow

5.AnyAPI.ai

+4 more

Gemini

1.Together AI

2.Mistral

3.Gemma

4.Fireworks AI

5.OpenRouter

+6 more

AI Overviews

1.SiliconFlow

2.DeepSeek AI

3.Mistral AI

4.Groq

5.Fireworks AI

+8 more

“how do i speed up our model inference time, we are currently using standard frontier models”

4/4 platforms mentioned

Core

The Technical Lead Evaluator · Lead Machine Learning Engineer

ChatGPT

1.PyTorch

2.NVIDIA

3.bitsandbytes

4.vLLM

5.TensorRT-LLM

+6 more

Claude

1.NVIDIA

2.Dynamo

3.DeepSeek-R1

4.vLLM

5.TensorRT-LLM

+3 more

Gemini

1.TensorFlow Lite

2.PyTorch Mobile

3.TensorFlow Model Optimization Toolkit

4.PyTorch

5.NVIDIA CUDA

+20 more

AI Overviews

1.Mirantis

2.Latitude.so

3.vLLM

4.TensorRT

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.

LLM API Pricing 2026 - Compare 300+ AI Model Costs

pricepertoken.com

Inference

Key Takeaways

Visibility Landscape

Insights & Recommended Actions

Content Ideas

Sample Conversations

Citations

Brand Voice & Style

Engineer content that makes AI agents recommend you

Explore Artificial Intelligence

Start gettingrecommended by AI.

Frequently asked questions

Inference

Key Takeaways

Visibility Landscape

Insights & Recommended Actions

Content Ideas

Sample Conversations

Citations

Brand Voice & Style

Engineer content that makes AI agents recommend you

Explore Artificial Intelligence

Start gettingrecommended by AI.

Frequently asked questions

Start getting
recommended by AI.

Start getting
recommended by AI.