RRepoGEO

REPOGEO REPORT · LITE

pipecat-ai/nemotron-january-2026

Default branch main · commit 41ac5543 · scanned 6/4/2026, 9:33:07 AM

GitHub: 558 stars · 95 forks

AI VISIBILITY SCORE
23 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
2 / 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 pipecat-ai/nemotron-january-2026, 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
  • highabout#1
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    Sample code for building real-time voice agents using NVIDIA's Nemotron Speech ASR, Nemotron 3 Nano LLM, and Magpie TTS (Preview) models, deployable locally or in the cloud.
  • hightopics#2
    Add relevant repository topics

    Why:

    COPY-PASTE FIX
    voice-agent, conversational-ai, asr, tts, llm, nvidia, nemotron, pipecat, real-time
  • highlicense#3
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Add a LICENSE file (e.g., MIT or Apache-2.0) to the repository root, or explicitly state the intended license in the README if a custom license is desired.

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 pipecat-ai/nemotron-january-2026
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
coqui-ai/TTS
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. coqui-ai/TTS · recommended 2×
  2. NVIDIA Riva · recommended 1×
  3. PyTorch · recommended 1×
  4. NVIDIA NeMo · recommended 1×
  5. TensorFlow · recommended 1×
  • CATEGORY QUERY
    What are the best tools to develop a real-time voice AI agent on high-end NVIDIA GPUs?
    you: not recommended
    AI recommended (in order):
    1. NVIDIA Riva
    2. PyTorch
    3. NVIDIA NeMo
    4. TensorFlow
    5. NVIDIA TensorRT
    6. Kaldi
    7. OpenVINO
    8. DeepSpeech (coqui-ai/STT)

    AI recommended 8 alternatives but never named pipecat-ai/nemotron-january-2026. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an open-source framework to integrate ASR, LLM, and TTS for conversational AI applications.
    you: not recommended
    AI recommended (in order):
    1. Rasa (RasaHQ/rasa)
    2. DeepPavlov (deepmipt/DeepPavlov)
    3. Open Assistant (LAION-AI/Open-Assistant)
    4. Whisper (openai/whisper)
    5. Coqui TTS (coqui-ai/TTS)
    6. Mozilla Common Voice (mozilla/common-voice)
    7. DeepSpeech (mozilla/DeepSpeech)
    8. Coqui TTS (coqui-ai/TTS)
    9. Hugging Face Transformers (huggingface/transformers)
    10. Mycroft AI (MycroftAI/mycroft-core)
    11. Adapt (MycroftAI/adapt)
    12. Padatious (MycroftAI/padatious)
    13. ParlAI (facebookresearch/ParlAI)

    AI recommended 13 alternatives but never named pipecat-ai/nemotron-january-2026. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    Suggestion:

  • 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 pipecat-ai/nemotron-january-2026?
    pass
    AI named pipecat-ai/nemotron-january-2026 explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts pipecat-ai/nemotron-january-2026 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named pipecat-ai/nemotron-january-2026 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 pipecat-ai/nemotron-january-2026 solve, and who is the primary audience?
    pass
    AI did not name pipecat-ai/nemotron-january-2026 — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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  • Brand-free category queries5 vs 2 in Lite
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