RRepoGEO

REPOGEO REPORT · LITE

Lagrange-Labs/deep-prove

Default branch master · commit 9d1a53e2 · scanned 6/23/2026, 6:08:05 PM

GitHub: 3,350 stars · 97 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
33 /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
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 Lagrange-Labs/deep-prove, 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
  • highreadme#1
    Reposition the README's opening statement to emphasize unique differentiators

    Why:

    CURRENT
    # DeepProve

Zero-knowledge proof system for neural network inference, with first-class support for end-to-end LLM proving.
    COPY-PASTE FIX
    # DeepProve

The first end-to-end zero-knowledge proof system for full LLM inference, generating cryptographic proofs of neural network forward passes orders of magnitude faster than circuit-based approaches.
  • mediumtopics#2
    Add more specific topics to improve category matching

    Why:

    CURRENT
    ai, ml, zk, zk-snarks, zkml
    COPY-PASTE FIX
    ai, ml, zk, zk-snarks, zkml, llm, large-language-models, inference-proving, zk-llm, verifiable-ai, fast-zkp
  • lowreadme#3
    Clarify the project's license directly in the README

    Why:

    COPY-PASTE FIX
    ## License

This project is licensed under the terms detailed in the `LICENSE` file, which outlines the specific conditions for use and distribution.

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 Lagrange-Labs/deep-prove
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
zkonnx/ezkl
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. zkonnx/ezkl · recommended 1×
  2. risc0/risc0 · recommended 1×
  3. zcash/halo2 · recommended 1×
  4. ingonyama-blst/orion · recommended 1×
  5. ConsenSys/gnark · recommended 1×
  • CATEGORY QUERY
    Looking for a zero-knowledge proof system to verify neural network inference efficiently.
    you: not recommended
    AI recommended (in order):
    1. EZKL (zkonnx/ezkl)
    2. RISC Zero (risc0/risc0)
    3. Halo2 (zcash/halo2)
    4. Orion (ingonyama-blst/orion)
    5. Gnark (ConsenSys/gnark)

    AI recommended 5 alternatives but never named Lagrange-Labs/deep-prove. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools can cryptographically prove large language model inference quickly and securely?
    you: not recommended
    AI recommended (in order):
    1. Giza
    2. RISC Zero
    3. Polygon Miden
    4. Scroll's zkEVM
    5. Halo2
    6. PSE's ZK-SNARKs
    7. SnarkyJS
    8. Mina Protocol
    9. Ezkl

    AI recommended 9 alternatives but never named Lagrange-Labs/deep-prove. 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 Lagrange-Labs/deep-prove?
    pass
    AI did not name Lagrange-Labs/deep-prove — 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 Lagrange-Labs/deep-prove in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Lagrange-Labs/deep-prove 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 Lagrange-Labs/deep-prove solve, and who is the primary audience?
    pass
    AI named Lagrange-Labs/deep-prove 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 Lagrange-Labs/deep-prove. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/Lagrange-Labs/deep-prove.svg)](https://repogeo.com/en/r/Lagrange-Labs/deep-prove)
HTML
<a href="https://repogeo.com/en/r/Lagrange-Labs/deep-prove"><img src="https://repogeo.com/badge/Lagrange-Labs/deep-prove.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

Lagrange-Labs/deep-prove — 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
Lagrange-Labs/deep-prove — RepoGEO report