REPOGEO REPORT · LITE

google/fully-homomorphic-encryption

Default branch main · commit 2ee88f40 · scanned 5/25/2026, 10:22:31 AM

GitHub: 3,629 stars · 267 forks

AI VISIBILITY SCORE

22 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

1 pass · 1 warn · 0 fail

Objective metadata checks

AI knows your name

1 / 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 google/fully-homomorphic-encryption, 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 README opening to clearly state project's role as a C++ FHE compiler toolchain

Why:

CURRENT

The FHE Team at Google, in partnership with multiple collaborators, is working to Unlock Fully Homomorphic Encryption for Google and the world. - Make it Easy - Make it Fast - at Scale What started with a C++ transpiler, has morphed into two new libraries: - HEIR is the new development platform and compiler toolchain for converting existing models to their FHE versions supporting multiple FHE schemes and backends. - Jaxite is a fully homomorphic encryption backend targeting TPUs and GPUs, written in JAX.

COPY-PASTE FIX

This repository provides HEIR, a C++ compiler toolchain and development platform for Fully Homomorphic Encryption (FHE). It enables converting existing C++ models to FHE versions, supporting multiple schemes and backends. Developed by the FHE Team at Google, our mission is to make FHE easy, fast, and scalable. The project also includes Jaxite, an FHE backend targeting TPUs and GPUs, written in JAX.

mediumhomepage#2

Add a homepage URL to the repository metadata

Why:

COPY-PASTE FIX

https://google.github.io/fully-homomorphic-encryption/ (or a more specific project/documentation URL if available)

lowabout#3
Expand the 'About' description to include 'toolchain' and 'development platform'
Why:
CURRENT
```
An FHE compiler for C++
```
COPY-PASTE FIX
```
An FHE compiler toolchain and development platform for C++ applications.
```

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 google/fully-homomorphic-encryption

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

SEAL

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

SEAL · recommended 2×
OpenFHE · recommended 2×
HElib · recommended 1×
PALISADE · recommended 1×
Concrete · recommended 1×

CATEGORY QUERY
What are the best FHE compilers for C++ applications requiring strong privacy guarantees?
you: not recommended
AI recommended (in order):
1. SEAL
2. HElib
3. PALISADE
4. OpenFHE
5. Concrete
AI recommended 5 alternatives but never named google/fully-homomorphic-encryption. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Looking for a compiler to enable privacy-preserving computation on C++ models at scale.
you: not recommended
AI recommended (in order):
1. SEAL
2. TFHE
3. EMP-toolkit
4. FHEW/APRA
5. OpenFHE
6. Intel SGX SDK
7. Apache Flink
AI recommended 7 alternatives but never named google/fully-homomorphic-encryption. This is the gap to close.
Show full AI answer

Objective checks

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

Metadata completeness
warn
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 google/fully-homomorphic-encryption?
pass
AI did not name google/fully-homomorphic-encryption — 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 google/fully-homomorphic-encryption in production, what risks or prerequisites should they evaluate first?
pass
AI named google/fully-homomorphic-encryption 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 google/fully-homomorphic-encryption solve, and who is the primary audience?
pass
AI did not name google/fully-homomorphic-encryption — 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 google/fully-homomorphic-encryption. 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

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/google/fully-homomorphic-encryption.svg)](https://repogeo.com/en/r/google/fully-homomorphic-encryption)

HTML

<a href="https://repogeo.com/en/r/google/fully-homomorphic-encryption"><img src="https://repogeo.com/badge/google/fully-homomorphic-encryption.svg" alt="RepoGEO" /></a>

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google/fully-homomorphic-encryption — 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