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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Moonshine AI

Visibility17

Vibe91

Businesses/Artificial Intelligence/Moonshine AI

AI Visibility & Sentiment

Moonshine AI

Moonshine AI develops privacy-focused voice interface technology that runs entirely on-device. Founded by pioneers from the original TensorFlow team, they offer Moonshine Voice, an open-source library for building live speech applications with industry-leading accuracy and speed.

Active Monitoring

usefulsensors.com

Artificial Intelligence Startups

AI Visibility Score

17/100

Invisible

Sentiment Score

91/100

AI Perception

Summary

Moonshine AI is currently a niche specialist, commanding a dominant 60% mention rate among Embedded Systems Leads while remaining virtually invisible to the high-value Privacy-First CTO and Indie Developer segments. While Claude recognizes the brand as a top-tier solution for on-device speech software, the brand is being systematically crowded out of broader 'offline voice' conversations by incumbents like Vosk and Whisper.

Value Proposition

The world's best library for building live speech applications that runs entirely on-device, offering superior accuracy to Whisper Large v3, lightning-fast streaming, cross-platform support, and complete data privacy—all open-source under MIT license.

Overview

Mission

To empower individuals and developers with private, powerful, and accessible AI tools, believing that your data should remain yours and that cutting-edge technology can be both innovative and respectful of privacy.

Products & Services

Moonshine Voice speech recognition libraryOn-device streaming speech modelsCross-platform SDKs (iOS, Android, Python, MacOS, Windows, Linux)Wearables and Raspberry Pi integration packagesOpen-source developer tools

Agent Breakdown

AI Platforms

How often do different AI platforms reference Moonshine AI?

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Conversation Analysis

Topics

What conversations is Moonshine AI included in — or excluded from?

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Buyer Personas

Personas

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

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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

Private & Offline Voice Integration(3 queries)

“how to build a voice assistant that works completely offline for a privacy app”

0/4 platforms mentioned

ChatGPT

1.Porcupine

2.Picovoice

3.Snowboy

4.TensorFlow Lite

5.WebRTC VAD

+27 more

Claude

1.Vosk

2.Pocketsphinx

3.Coqui STT

4.Mozilla

5.Whisper

+11 more

Gemini

1.Alexa

2.Google Assistant

3.Porcupine

4.Picovoice

5.Precise

+20 more

AI Overviews

1.switchboard.audio

“best libraries for on-device speech to text that don't need an internet connection”

0/3 platforms mentioned

Claude

1.Whisper.cpp

2.Whisper

3.Vosk

4.Kaldi

5.PocketSphinx

+4 more

Gemini

1.Whisper API

2.whisper.cpp

3.Whisper

4.Core ML

5.CUDA

+12 more

AI Overviews

1.Whisper

2.Whisper.cpp

3.faster-whisper

4.CTranslate2

5.Vosk

+14 more

“help me pick an offline speech library for a secure app, give me some specific brand recommendations”

0/4 platforms mentioned

ChatGPT

1.NVIDIA Riva

2.wav2vec 2.0

3.Hugging Face

4.FAIR

5.ONNX

+20 more

Claude

1.Vosk

2.Coqui STT

3.Mozilla

4.Kaldi

5.Silero Models

Gemini

1.Whisper

2.NVIDIA A100

3.Apple M2 Max

4.Faster-Whisper

5.CTranslate2

+12 more

AI Overviews

1.Vosk

2.GitHub

3.Alpha Cephei

4.Whisper

5.whisper.cpp

+9 more

Embedded Systems & IoT Development(1 query)

“what are the best speech recognition models for a raspberry pi project”

1/4 platforms mentioned

ChatGPT

1.Raspberry Pi

2.Vosk

3.Kaldi

4.Whisper

5.whisper.cpp

+21 more

Claude

1.Raspberry Pi

2.Porcupine

3.Picovoice

4.Vosk

5.PocketSphinx

+2 more

Gemini

1.Raspberry Pi

2.ARM

3.Vosk

4.Kaldi

5.Whisper.cpp

+11 more

AI Overviews

1.Raspberry Pi

2.Whisper

3.Resemble AI

4.Whisper.cpp

5.Faster-Whisper

7.Moonshine

+2 more

Evaluating On Device Speech Technology(1 query)

“who makes the most reliable on-device speech recognition software right now”

0/4 platforms mentioned

ChatGPT

1.Speech framework

2.Siri

3.Apple Neural Engine

4.Speech Services

5.ML Kit

+21 more

Claude

1.Apple Siri

2.Whisper

3.Pocketsphinx

4.Kaldi

5.Vosk

Gemini

1.Whisper

2.Whisper.cpp

3.Core ML

4.Pixel

5.Android

+13 more

AI Overviews

1.Whisper

2.Nuance

3.Dragon Professional

4.Voicy Speech to Text

5.Apple Dictation

+2 more

Building High Performance Live Voice Apps(1 query)

“best sdk for adding live speech to text to a cross platform mobile app”

0/4 platforms mentioned

ChatGPT

1.Microsoft Azure Speech SDK

2.Google Cloud Speech-to-Text

3.Deepgram

4.Vosk

5.Whisper

+10 more

Claude

1.Google Cloud Speech-to-Text

2.Azure Cognitive Services Speech-to-Text

3.Deepgram

4.AssemblyAI

5.Speechmatics

+5 more

Gemini

1.Deepgram

2.Google Cloud Speech-to-Text

3.Chirp

4.Firebase

5.Vosk

+6 more

AI Overviews

1.Deepgram Nova-2

2.AssemblyAI Universal-Streaming

3.Azure AI Speech SDK

4.Google Cloud Speech-to-Text

5.Chirp

+4 more

Analysis

Key Insights

What AI visibility analysis reveals about this brand

Strength

High authority in specialized technical circles, specifically the Embedded Systems Lead persona where mention rates hit 60%.

Strength

Strong brand sentiment and top-ranking performance (Pos #1) on Claude and Gemini when users specifically look for 'brand vibe checks' or on-device speech software evaluations.

Strength

Effective penetration of AIOverviews for niche hardware queries like Raspberry Pi and IoT development.

Gap

Zero visibility among Privacy-First CTOs and Solo Indie App Developers, two critical buyer personas for secure, offline AI.

Gap

Persistent absence in 'Private & Offline Voice Integration' queries, which is the core use case for the product.

Gap

Significantly trailing competitors like Vosk and Whisper.cpp who appear 3-4x more frequently in general speech-to-text library recommendations.

Opportunity

Displace Vosk and Whisper.cpp by creating comparative technical documentation that highlights Moonshine's advantages in 'offline' and 'on-device' scenarios.

Opportunity

Capture the 'Privacy-First' narrative by targeting CTO-level queries regarding data sovereignty and secure voice SDKs.

Opportunity

Improve Gemini performance, which currently shows a dismal average position of 11.5 compared to Claude's 3.5.

Technical Health

Site Health for AI Visibility

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

83/100

13 passed 5 warnings 1 issues

Audited 3/2/2026

Crawlability83

Can AI bots find your pages?

Technical96

SSL, mobile, doctype basics

On-Page SEO93

Titles, descriptions, headings

Content Quality47

Word count, depth, freshness

Schema Markup85

Structured data for AI comprehension

Social & OG82

Open Graph, Twitter cards

AI Readability60

How well AI can parse your content

Critical Issues

Content is too thin

Expand your content to at least 300-500 words with valuable information.

Warnings

No robots.txt file found

Create a robots.txt file at your domain root. Optional but recommended.

2 render-blocking resource(s) detected

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

Title is too short (12 characters)

Expand the title to 50-60 characters with descriptive keywords.

Few internal links on this page

Add more internal links to related pages on your site.

Missing Open Graph tags for social sharing

Add og:title, og:description, and og:image meta tags.

Want a full technical audit with AI-specific recommendations?

Run a free visibility scan

Brand Identity

Brand Voice & Style

How AI perceives Moonshine AI's communication style and personality

Moonshine AI communicates with technical credibility balanced by approachable simplicity. The brand voice is confident yet humble, emphasizing democratization and accessibility over exclusivity. They use clear, jargon-light language that makes complex AI concepts feel achievable for any developer. There's an underlying ethos of privacy advocacy and open-source community values, presented without preachiness. The tone is optimistic about technology's potential while grounded in practical, measurable benefits.

Core Tone Traits

Technically Credible

Backs claims with benchmarks and references to HuggingFace leaderboards and research papers

Accessible & Inclusive

Uses phrases like 'no PhD required' and 'for everyone' to lower barriers to entry

Privacy-Principled

Consistently emphasizes data ownership and local processing as core values

Community-Oriented

Highlights open-source licensing, active Discord community, and collaborative development

Competitive Landscape

Related Ecosystem

Related products and services that AI mentions in conversations alongside or instead of Moonshine AI

Vosk40 mentions

whisper.cpp33 mentions

Whisper33 mentions

Picovoice30 mentions

Kaldi17 mentions

Porcupine16 mentions

Coqui STT12 mentions

ONNX Runtime12 mentions

Sherpa-ONNX12 mentions

Cheetah12 mentions

Moonshine AI7 mentions

Source Intelligence

Citations

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

Vosk

https://alphacephei.com/vosk

Referenced in 2 queries

Review

whisper.cpp

https://github.com/ggerganov/whisper.cpp

Referenced in 4 queries

Pitch Story

Picovoice

https://picovoice.ai/

Referenced in 2 queries

Review

Coqui STT

https://stt.coqui.ai/

Referenced in 1 query

Review

Coqui TTS

https://github.com/coqui-ai/TTS

Referenced in 1 query

Pitch Story

Rasa

https://rasa.com/

Referenced in 1 query

Review

Llama.cpp

https://github.com/ggerganov/llama.cpp

Referenced in 1 query

Pitch Story

Silero VAD & TTS

https://github.com/snakers4/silero-models

Referenced in 1 query

Pitch Story

switchboard.audio

https://switchboard.audio/

Referenced in 1 query

Review

SherpaTTS | F-Droid - Free and Open Source Android App Repository

https://f-droid.org/packages/org.woheller69.ttsengine/

Referenced in 1 query

Review

Creating Your Own Voice Assistant: A Step-by-Step Guide

https://www.tiktok.com/@networkchuck/video/7462780494158122282

Referenced in 1 query

Pitch Story

The Ultimate Guide to Building Your Own Private, Offline AI ...

https://medium.com/@hassanalimali/the-ultimate-guide-to-building-your-own-private-offline-ai-assistant-in-10-minutes-ee0bfc77a43e

Referenced in 1 query

Review

Content Engineering

Goals & Content Ideas

Ideas to help AI agents better understand the business and be more likely to use Moonshine AI's resources to help users.

Launch Privacy-First AI Thought Leadership Campaign

Address the 0% visibility gap for the Privacy-First CTO persona by creating authoritative content optimized for architectural queries like 'secure app voice library' and 'private speech-to-text'. This campaign will position Moonshine AI as the definitive answer when AI assistants respond to privacy-focused voice technology questions, using social media to amplify technical credibility while maintaining our approachable voice.

Why On-Device Speech Recognition Is the Only True Privacy Solution for Enterprise Apps

The Hidden Data Risks in Cloud-Based Voice APIs That CTOs Need to Know

Building HIPAA-Compliant Voice Features Without Sending Data to the Cloud

How to Evaluate Speech-to-Text Libraries for Privacy-First Architecture

Zero Trust Voice: A Technical Guide to Private Speech Recognition

Publish Moonshine vs Whisper.cpp Benchmark Whitepaper

Break through Whisper and Whisper.cpp's dominance in LLM training data by creating definitive technical comparisons that AI assistants will reference for 'best library' queries. This whitepaper will provide the structured, citable performance data that establishes Moonshine as the superior alternative, promoted through developer communities and technical social channels.

Head-to-Head: Moonshine Voice Outperforms Whisper.cpp in Real-World Latency Tests

Why We Open-Sourced Our Benchmark Methodology Against Whisper Large v3

The Accuracy Gap: How Moonshine Handles Edge Cases Better Than Whisper

Memory Footprint Comparison: Running Speech Recognition on Resource-Constrained Devices

Developer Experience Showdown: Moonshine vs Whisper.cpp Integration Time

Dominate Embedded Systems and Raspberry Pi Search

Double down on the embedded systems niche where AIOverviews already shows interest and competitors are less entrenched. Create optimized technical documentation and content targeting 'Raspberry Pi' and 'Embedded IoT' keywords to build an unassailable moat in this growing market segment, sharing practical tutorials and success stories across developer platforms.

Complete Guide: Running Moonshine Voice on Raspberry Pi Zero 2 W

Building a Privacy-First Smart Home Assistant with On-Device Speech Recognition

Benchmark Results: Speech Recognition Performance Across Popular IoT Boards

How to Add Voice Commands to Any Arduino Project Without Cloud Dependencies

Real-Time Transcription on Edge Devices: A Step-by-Step Implementation Guide

Standardize Technical Citations Across Developer Forums

Improve Moonshine's 11.5 average position on Gemini by creating consistent, structured brand mentions across GitHub, Stack Overflow, and technical forums that AI engines use to verify product authority. This systematic approach ensures our technical contributions are properly attributed and discoverable when developers ask AI assistants for recommendations.

Contributing to Open Source: Our Philosophy on Community-First Documentation

Common Speech Recognition Implementation Mistakes and How to Avoid Them

Answering the Top 10 Questions Developers Ask About On-Device ASR

How We Structure Our GitHub Repository for Maximum Developer Accessibility

Best Practices for Integrating Moonshine Voice Into Existing Codebases

Content Engineering

Recommended Actions

Launch a 'Privacy-First AI' content series optimized for architectural queries like 'secure app voice library' and 'private speech-to-text'.

Currently, the Privacy-First CTO persona has 0% visibility; this content will bridge the gap between technical capability and executive requirements.

Impact: High

Develop and distribute a 'Moonshine AI vs. Whisper.cpp' performance benchmark whitepaper.

Whisper and Whisper.cpp are the primary obstacles to visibility; direct technical comparisons are required to break into the LLM training sets for 'best library' queries.

Impact: High

Optimize technical documentation specifically for the 'Raspberry Pi' and 'Embedded IoT' keywords where AIOverviews is already showing interest.

Moonshine AI is already showing strength in embedded systems; doubling down here ensures a 'moat' in a niche where competitors are less entrenched.

Impact: Medium

Standardize brand mentions across technical forums and GitHub to improve the 11.5 average position on Gemini.

Gemini’s low ranking suggests a lack of structured technical citations that the engine uses to verify product authority.

Impact: Medium

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