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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RunAnywhere

Visibility0

Vibe75

Businesses/Software/RunAnywhere

AI Visibility & Sentiment

RunAnywhere

RunAnywhere is a Y Combinator-backed company that provides on-device AI infrastructure for mobile and edge applications. They offer SDKs that enable developers to deploy fast, private AI models including LLMs, speech-to-text, text-to-speech, and vision models directly on iOS, Android, and edge devices with minimal code integration.

Active Monitoring

runanywhere.ai

Software YC25-26

AI Visibility Score

0/100

Invisible

Sentiment Score

75/100

Score by Reach

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

AI Perception

Key Takeaways

How AI platforms collectively perceive and describe RunAnywhere today.

RunAnywhere currently functions as a 'phantom brand' within the AI ecosystem: while leading LLMs like Claude and Gemini recognize the company in direct 'vibe checks,' they fail to recommend the brand for a single functional industry query. This disconnect indicates that while the brand is indexed, its technical utility is completely absent from the decision-making pathways used by Enterprise Fleet Architects and Fintech CTOs, leaving the field open for competitors like TensorFlow Lite and ExecuTorch.

Value Proposition

Deploy fast, private AI models across iOS, Android, and edge devices with just a few lines of code, featuring cost-effective on-device inference, 3-minute setup, privacy-focused architecture, and enterprise-grade fleet management through a unified SDK and control plane.

Overview

Mission

Enabling developers to run AI anywhere with privacy-first, low-latency on-device inference that keeps user data secure while delivering instant AI capabilities.

Products & Services

On-Device AI SDK for iOS and AndroidLLM, STT, TTS, and Vision model inferenceControl Plane for fleet management and OTA updatesPolicy-based routing between on-device and cloudUsage analytics and monitoring dashboard

Current State

Visibility Landscape

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

	ChatGPT	Claude	Gemini	AI Overviews
Reputation Brand recognition & direct queries	0	0	0	0
Core Topics Product/service category queries	—	—	—	—
Growth Areas Adjacent, aspirational & visionary	—	—	—	—

ChatGPT

Claude

Gemini

AI Overviews

Reputation

Brand recognition & direct queries

Core Topics

Product/service category queries

—

Growth Areas

Adjacent, aspirational & visionary

—

Competitive Landscape

TensorFlow Lite

23 mentions

MediaPipe

18 mentions

ExecuTorch

17 mentions

PyTorch Mobile

13 mentions

Core ML

13 mentions

ONNX Runtime

11 mentions

Loading visibility matrix...

Analysis

Insights & Recommended Actions

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

Key Findings

Strength

Direct brand recognition in Claude, Gemini, and AI Overviews during brand-specific 'vibe check' queries, placing at position #1 when explicitly asked about.

Strength

Baseline indexing exists across multiple LLM architectures, suggesting the core brand identity is known even if its applications are not.

Gap

Zero visibility across critical technical categories including Local AI Development Strategy, Scalable AI Operations, and Hybrid Inference.

Recommended Actions

Publish technical 'How-To' documentation specifically targeting Hybrid Inference and Policy-Based Routing.

The data shows 0% visibility in these high-intent queries; technical guides provide the structured data LLMs need to recommend RunAnywhere as a solution rather than just a name.

Develop and index case studies focused on 'Privacy-First Mobile Apps' for the Fintech CTO persona.

RunAnywhere failed to appear in any privacy-centric queries despite this being a core industry requirement; specific persona-targeted content will trigger LLM associations with these high-value buyers.

Optimize technical documentation for 'OTA updates for AI models' to capture the Enterprise Fleet Architect audience.

This is a massive gap in the current visibility profile where competitors are currently winning by default due to a lack of alternative mentioned solutions.

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

Local AI Development Strategy(2 queries)

“help me find a way to run a small llm locally on android and ios without using cloud apis”

0/3 platforms mentioned

Core

Claude

1.Ollama

2.Mistral 7B

3.Llama 2

4.Mango

5.Enchanted

+14 more

Gemini

1.Layla

2.GGUF

3.Llama 3

4.Mistral

5.Private LLM

+22 more

AI Overviews

1.MLC Chat

2.MLC LLM

3.Llama 3

4.Mistral

5.AnythingLLM

+13 more

“what tools should i use to build a privacy-first mobile app that uses vision models offline”

0/4 platforms mentioned

Core

The Privacy-Obsessed Fintech CTO · Chief Technology Officer

ChatGPT

1.Core ML

2.coremltools

3.Metal

4.Neural Engine

5.TensorFlow Lite

+45 more

Claude

1.Core ML

2.Vision framework

3.TensorFlow Lite

4.MediaPipe

5.ONNX Runtime Mobile

+9 more

Gemini

1.Core ML

2.ExecuTorch

3.PyTorch

4.Qualcomm AI Stack

5.SNPE

+16 more

AI Overviews

1.Core ML

2.LiteRT

3.TensorFlow Lite

4.PyTorch Mobile

5.ExecuTorch

+11 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.

ollama.ai

Web1 ref

How to run Mistral LLM locally on iPhone or iPad

youtube.com

Video1 ref

How to Run LLMs Locally on Phone with ChatterUI App - AI ...

youtube.com

Video1 ref

Running an LLM on an Android Phone - Mostly nerdless

mostlynerdless.de

Web1 ref

How to Run and Deploy LLMs on your iOS or Android Phone

youtube.com

Video1 ref

AnythingLLM | The all-in-one AI application for everyone

anythingllm.com

Web1 ref

Private Mind - fully on device free LLM chat app for Android and iOS

reddit.com

Forum1 ref

LLM Inference guide for Android | Google AI Edge

ai.google.dev

Web1 ref

How to Install and Run LLMs Locally on Android Phones - KDnuggets

kdnuggets.com

Web1 ref

This AI Agent Runs LOCALLY on Your Phone - How to Use ...

youtube.com

Video1 ref

Locally AI - Run AI models locally on your iPhone, iPad, and Mac.

locallyai.app

Web1 ref

How to Run Local LLMs on Android: From Setup to Real ...

medium.com

Blog1 ref

MLC Chat - App Store - Apple

apps.apple.com

Web1 ref

Is there any LLM that can run directly on an Android phone - Reddit

reddit.com

Forum1 ref

Edge AI device management at scale — Use Case

foundries.io

Web1 ref

Competitive Landscape

Brands and products that AI platforms mention alongside or instead of RunAnywhere.

TensorFlow Lite23 mentions

MediaPipe18 mentions

ExecuTorch17 mentions

PyTorch Mobile13 mentions

Core ML13 mentions

ONNX Runtime11 mentions

llama.cpp9 mentions

MLC LLM9 mentions

PyTorch9 mentions

ONNX Runtime Mobile7 mentions

RunAnywhere0 mentions

Brand Identity

Brand Voice & Style

How AI perceives RunAnywhere's communication style and personality

RunAnywhere communicates with a developer-first, technically credible voice that balances expertise with accessibility. The tone is confident and forward-thinking, positioning the company as innovators in the edge AI space while remaining practical and solution-oriented. They speak directly to developers using familiar terminology, code examples, and clear value propositions. The brand avoids hype in favor of concrete benefits like latency reduction, privacy, and cost savings, maintaining a professional yet approachable demeanor that reflects their Y Combinator backing and engineering-led culture.

Core Tone Traits

Developer-First & Technical

Uses code snippets, SDK terminology, and engineering concepts naturally without over-explaining

Confident & Innovative

Positions as category leaders in on-device AI with forward-looking vision

Practical & Solution-Oriented

Focuses on concrete benefits, setup time, and real-world problem-solving

Approachable & Community-Driven

Invites collaboration through Discord, open source, and direct developer engagement

Backing

Investors

Y Combinator

Engineer content that makes AI agents recommend you

Pendium analyzes how AI platforms perceive your brand, reverse-engineers what they already cite, and continuously publishes content designed to fill gaps and earn more mentions — on autopilot, with you in the loop.

Data generated by Pendium.ai AI visibility scanning. Last scanned February 27, 2026.

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Frequently asked questions

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AI Visibility Score

RunAnywhere has an AI visibility score of 0/100, rated as invisible. This score reflects how often and how prominently RunAnywhere appears in responses from AI assistants like ChatGPT, Claude, and Gemini.

AI Perception Summary

Strengths

Direct brand recognition in Claude, Gemini, and AI Overviews during brand-specific 'vibe check' queries, placing at position #1 when explicitly asked about.
Baseline indexing exists across multiple LLM architectures, suggesting the core brand identity is known even if its applications are not.

Visibility Gaps

Zero visibility across critical technical categories including Local AI Development Strategy, Scalable AI Operations, and Hybrid Inference.
Complete failure to capture the 'Privacy-Obsessed Fintech CTO' persona, a segment where RunAnywhere's local-first positioning should theoretically dominate.
Total absence from fleet management and OTA update queries, allowing TensorFlow Lite and MediaPipe to monopolize the 'Enterprise Fleet Architect' audience.

Competitors in AI Recommendations

TensorFlow Lite: 23 mentions
MediaPipe: 18 mentions
ExecuTorch: 17 mentions
PyTorch Mobile: 13 mentions
Core ML: 13 mentions
ONNX Runtime: 11 mentions
llama.cpp: 9 mentions
MLC LLM: 9 mentions
PyTorch: 9 mentions
ONNX Runtime Mobile: 7 mentions
Llama 3: 6 mentions
Hugging Face: 6 mentions
Prometheus: 6 mentions
Mender: 6 mentions
Ollama: 5 mentions

Categories: Software

Tags: YC25-26