RunAnywhere

Visibility0

Vibe75

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

AI Perception

Summary

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

Agent Breakdown

AI Platforms

How often do different AI platforms reference RunAnywhere?

Loading explorer...

Conversation Analysis

Topics

What conversations is RunAnywhere included in — or excluded from?

Loading explorer...

Buyer Personas

Personas

Who does each AI platform recommend RunAnywhere to, and when?

Loading explorer...

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

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

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

Scalable AI Operations And Fleet Management(1 query)

“how can i handle ota updates for ai models across a huge fleet of edge devices”

0/4 platforms mentioned

ChatGPT

1.MLflow

2.Kubeflow

3.SageMaker

4.S3

5.CloudFront

+27 more

Claude

1.Mender

2.Balena Cloud

3.AWS IoT Greengrass

4.SageMaker Edge Manager

5.Eclipse hawkBit

+2 more

Gemini

1.TensorRT

2.NVIDIA

3.OpenVINO

4.Intel

5.ONNX

+20 more

AI Overviews

1.Runpod

2.ONNX Runtime

3.TensorRT

4.Docker

5.NVIDIA

+6 more

Hybrid Inference And Cost Optimization(1 query)

“how to set up policy-based routing to switch between local and cloud ai based on device battery or network”

0/4 platforms mentioned

ChatGPT

1.Envoy

2.Istio

3.Kubernetes

4.OPA

5.Traefik

+14 more

Claude

1.Linux

2.Android

3.TensorFlow Lite

4.iOS

5.ONNX Runtime

+8 more

Gemini

1.Ollama

2.LocalAI

3.GPT-4o

4.Groq

5.LiteLLM

+13 more

AI Overviews

1.Hewlett Packard Enterprise

2.Linux

3.macOS

4.Cisco

5.Google Cloud

Evaluating On Device AI Solutions(1 query)

“who are the most trusted providers for on-device ai sdks that work on both ios and android”

0/4 platforms mentioned

ChatGPT

1.TensorFlow Lite

2.PyTorch Mobile

3.ONNX Runtime Mobile

4.TensorFlow Lite Micro

5.EdgeTPU

+19 more

Claude

1.Google ML Kit

2.Firebase

3.TensorFlow Lite

4.PyTorch Mobile

5.Core ML

+4 more

Gemini

1.TensorFlow Lite

2.MediaPipe

3.ML Kit

4.ONNX Runtime

5.ExecuTorch

+9 more

AI Overviews

1.LiteRT

2.TensorFlow Lite

3.ExecuTorch

4.PyTorch Mobile

5.Google ML Kit

+7 more

Analysis

Key Insights

What AI visibility analysis reveals about this brand

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.

Gap

Complete failure to capture the 'Privacy-Obsessed Fintech CTO' persona, a segment where RunAnywhere's local-first positioning should theoretically dominate.

Gap

Total absence from fleet management and OTA update queries, allowing TensorFlow Lite and MediaPipe to monopolize the 'Enterprise Fleet Architect' audience.

Opportunity

Bridge the 'utility gap' by connecting the brand name to specific technical solutions like policy-based routing and on-device SDKs where competitors like llama.cpp are currently vulnerable.

Opportunity

Exploit the high mention rate of ExecuTorch and TensorFlow Lite by creating comparison-driven documentation that LLMs can ingest to associate RunAnywhere with these category leaders.

Technical Health

Site Health for AI Visibility

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

94/100

19 passed 2 warnings

Audited 2/27/2026

Crawlability96

Can AI bots find your pages?

Technical96

SSL, mobile, doctype basics

On-Page SEO93

Titles, descriptions, headings

Content Quality87

Word count, depth, freshness

Schema Markup85

Structured data for AI comprehension

Social & OG100

Open Graph, Twitter cards

AI Readability60

How well AI can parse your content

Warnings

2 render-blocking resource(s) detected

Consider deferring or async-loading non-critical scripts and stylesheets.

H3 used without H2 — heading levels are skipped

Use headings in order (H1 → H2 → H3). Don't skip levels.

Want a full technical audit with AI-specific recommendations?

Run a free visibility scan

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

Competitive Landscape

Related Ecosystem

Related products and services that AI mentions in conversations 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

Source Intelligence

Citations

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

ollama.ai

https://ollama.ai/

Referenced in 1 query

Review

How to run Mistral LLM locally on iPhone or iPad

https://www.youtube.com/watch?v=5QEDNZlDf-c

Referenced in 1 query

Pitch Story

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

https://www.youtube.com/watch?v=yHumQmSkLhE&t=21

Referenced in 1 query

Pitch Story

Running an LLM on an Android Phone - Mostly nerdless

https://mostlynerdless.de/blog/2025/11/05/running-an-llm-on-an-android-phone/

Referenced in 1 query

Review

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

https://www.youtube.com/watch?v=sBfN7XvvZEo

Referenced in 1 query

Pitch Story

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

https://anythingllm.com/

Referenced in 1 query

Review

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

https://www.reddit.com/r/LocalLLM/comments/1m6aum3/private_mind_fully_on_device_free_llm_chat_app/

Referenced in 1 query

Join Discussion

LLM Inference guide for Android | Google AI Edge

https://ai.google.dev/edge/mediapipe/solutions/genai/llm_inference/android

Referenced in 1 query

Review

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

https://www.kdnuggets.com/install-run-llms-locally-android-phones

Referenced in 1 query

Review

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

https://www.youtube.com/watch?v=HuzuqZAX2vM

Referenced in 1 query

Pitch Story

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

https://locallyai.app/

Referenced in 1 query

Review

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

https://medium.com/@maydin/how-to-run-local-llms-on-android-from-setup-to-real-world-use-cases-12f29f969bf8

Referenced in 1 query

Review

Content Engineering

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.

Impact: High

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.

Impact: High

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.

Impact: Medium

Create a 'RunAnywhere vs. ExecuTorch/TensorFlow Lite' competitive matrix on the primary domain.

LLMs frequently use competitive comparisons to determine brand relevance; this will help pivot RunAnywhere from an unknown entity to a direct alternative in established categories.

Impact: Medium

Is this your business? We can help you improve your AI visibility.

Book a Free Strategy Session

Backing

Investors

Y Combinator

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

Explore Software

Start getting recommended by AI

Enter your website to see exactly what ChatGPT, Claude, and Gemini say about your business. Free, instant, and eye-opening.

Free visibility scanResults in 2 minutesNo credit card required

Frequently asked questions

Don't see your question? Book a demo and we'll walk you through it.

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