REPOGEO REPORT · LITE

FluidInference/FluidAudio

Default branch main · commit 4b4e3ddf · scanned 6/18/2026, 4:47:09 AM

GitHub: 2,284 stars · 316 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE

40 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

2 pass · 0 warn · 0 fail

Objective metadata checks

AI knows your name

3 / 3

Direct prompts that named your repo

HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface FluidInference/FluidAudio, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION

hightopics#1

Remove the 'nvidia' topic

Why:

CURRENT

ane, asr, audio, automatic-speech-recognition, avfoundation, coreml, ios, macos, nvidia, parakeet, real-time, speaker-diarization, speaker-embedding, speaker-identification, speaker-recognition, speech-to-text, swift, vad, voice-activity-detection

COPY-PASTE FIX

ane, asr, audio, automatic-speech-recognition, avfoundation, coreml, ios, macos, parakeet, real-time, speaker-diarization, speaker-embedding, speaker-identification, speaker-recognition, speech-to-text, swift, vad, voice-activity-detection

highreadme#2

Add a concise tagline to the README introduction

Why:

CURRENT

# FluidAudio - Transcription, Text-to-speech, VAD, Speaker diarization with CoreML Models

[](https://swift.org)
[](https://developer.apple.com)

COPY-PASTE FIX

# FluidAudio - Transcription, Text-to-speech, VAD, Speaker diarization with CoreML Models

**The Swift SDK for real-time, on-device audio AI on Apple devices, powered by CoreML and the ANE.**

[](https://swift.org)
[](https://developer.apple.com)

mediumreadme#3

Emphasize 'Pure Swift' in the README's first paragraph

Why:

CURRENT

FluidAudio is a Swift SDK for fully local, low-latency audio AI on Apple devices, with inference offloaded to the Apple Neural Engine (ANE), resulting in less memory and generally faster inference.

COPY-PASTE FIX

FluidAudio is a **pure Swift SDK** for fully local, low-latency audio AI on Apple devices, with inference offloaded to the Apple Neural Engine (ANE), resulting in less memory and generally faster inference.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall

0 / 2

0% of queries surface FluidInference/FluidAudio

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

SFSpeechRecognizer

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

SFSpeechRecognizer · recommended 1×
Whisper · recommended 1×
coremltools · recommended 1×
ECAPA-TDNN · recommended 1×
PyTorch · recommended 1×

CATEGORY QUERY
How to perform real-time speech-to-text and diarization on iOS devices using CoreML?
you: not recommended
AI recommended (in order):
1. SFSpeechRecognizer
2. Whisper
3. coremltools
4. ECAPA-TDNN
5. PyTorch
6. TensorFlow
7. SpeechBrain
8. pyannote.audio
9. AVAudioEngine
10. AVCaptureSession
AI recommended 10 alternatives but never named FluidInference/FluidAudio. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Looking for an SDK for on-device voice activity detection and transcription without cloud APIs.
you: not recommended
AI recommended (in order):
1. Picovoice Porcupine
2. Picovoice Rhino
3. Mozilla DeepSpeech
4. WebRTC VAD
5. Vosk
6. OpenVINO
7. TensorFlow Lite
AI recommended 7 alternatives but never named FluidInference/FluidAudio. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
pass
README presence
pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

Compared to common alternatives in this category, what is the core differentiator of FluidInference/FluidAudio?
pass
AI named FluidInference/FluidAudio explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts FluidInference/FluidAudio in production, what risks or prerequisites should they evaluate first?
pass
AI named FluidInference/FluidAudio explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
In one sentence, what problem does the repo FluidInference/FluidAudio solve, and who is the primary audience?
pass
AI named FluidInference/FluidAudio explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of FluidInference/FluidAudio. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/FluidInference/FluidAudio.svg)](https://repogeo.com/en/r/FluidInference/FluidAudio)

HTML

<a href="https://repogeo.com/en/r/FluidInference/FluidAudio"><img src="https://repogeo.com/badge/FluidInference/FluidAudio.svg" alt="RepoGEO" /></a>

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FluidInference/FluidAudio — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite