REPOGEO REPORT · LITE
sentient-agi/OML-1.0-Fingerprinting
Default branch main · commit e3ee78ce · scanned 6/30/2026, 3:36:52 PM
GitHub: 3,506 stars · 233 forks
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.
2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).
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 sentient-agi/OML-1.0-Fingerprinting, 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.
- highreadme#1Reposition README's opening paragraph to emphasize LLM ownership and protection
Why:
CURRENTWelcome to OML 1.0: Fingerprinting. This repository houses the tooling for generating and embedding secret fingerprints into LLMs through fine-tuning to enable identification of LLM ownership and protection against unauthorized use.
COPY-PASTE FIXOML 1.0: Fingerprinting provides the essential tooling for embedding secret, verifiable fingerprints directly into Large Language Models (LLMs) via fine-tuning. This enables clear identification of LLM ownership and robust protection against unauthorized use, ensuring creators can assert provenance and control over their AI assets.
- mediumtopics#2Add more specific topics to improve category visibility
Why:
CURRENTfine-tuning, fingerprint, loyalty, oml, sentient, verifiable-ai
COPY-PASTE FIXfine-tuning, fingerprint, loyalty, oml, sentient, verifiable-ai, llm-security, model-provenance, intellectual-property, ai-ownership, digital-watermarking, ai-ethics
- lowhomepage#3Add the project's homepage URL to the repository metadata
Why:
COPY-PASTE FIXhttps://sentient.foundation/
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.
- OpenAI's Watermarking API · recommended 1×
- Awatermark · recommended 1×
- Invisible Watermark · recommended 1×
- Stego-LLM · recommended 1×
- wandb/wandb · recommended 1×
- CATEGORY QUERYHow to embed unique identifiers into large language models to prove ownership?you: not recommendedAI recommended (in order):
- OpenAI's Watermarking API
- Awatermark
- Invisible Watermark
- Stego-LLM
- Weights & Biases (wandb/wandb)
- MLflow (mlflow/mlflow)
AI recommended 6 alternatives but never named sentient-agi/OML-1.0-Fingerprinting. This is the gap to close.
Show full AI answer
- CATEGORY QUERYSeeking tools to detect and prevent unauthorized use of fine-tuned AI models.you: not recommendedAI recommended (in order):
- OpenVINO Model Server
- NVIDIA Triton Inference Server
- Azure Machine Learning
- AWS SageMaker
- Google Cloud AI Platform
- Weights & Biases (W&B)
- MLflow
- Microsoft Purview DLP
- Symantec DLP
- Aito.ai
- Amazon API Gateway
- Azure API Management
- Kong Gateway
- Docker
- Kubernetes
AI recommended 15 alternatives but never named sentient-agi/OML-1.0-Fingerprinting. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesswarn
Suggestion:
- README presencepass
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 sentient-agi/OML-1.0-Fingerprinting?passAI did not name sentient-agi/OML-1.0-Fingerprinting — 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?
- If a team adopts sentient-agi/OML-1.0-Fingerprinting in production, what risks or prerequisites should they evaluate first?passAI named sentient-agi/OML-1.0-Fingerprinting 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 sentient-agi/OML-1.0-Fingerprinting solve, and who is the primary audience?passAI did not name sentient-agi/OML-1.0-Fingerprinting — 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?
Embed your GEO score
Drop this badge into the README of sentient-agi/OML-1.0-Fingerprinting. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.
Live preview[](https://repogeo.com/en/r/sentient-agi/OML-1.0-Fingerprinting)<a href="https://repogeo.com/en/r/sentient-agi/OML-1.0-Fingerprinting"><img src="https://repogeo.com/badge/sentient-agi/OML-1.0-Fingerprinting.svg" alt="RepoGEO" /></a>Subscribe to Pro for deep diagnoses
sentient-agi/OML-1.0-Fingerprinting — 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