RRepoGEO

REPOGEO REPORT · LITE

spiculedata/saiku

Default branch development · commit 4f5cfc50 · scanned 5/24/2026, 10:57:04 AM

GitHub: 1,305 stars · 657 forks

AI VISIBILITY SCORE
35 /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
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 spiculedata/saiku, 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
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    olap, analytics, semantic-layer, data-cubes, mondrian, business-intelligence, ai-agents, data-exploration
  • mediumabout#2
    Update the repository description to reflect modern features

    Why:

    CURRENT
    Saiku Analytics - The Worlds Greatest Open Source OLAP Browser
    COPY-PASTE FIX
    Saiku Analytics: An open-source Semantic Layer and OLAP Browser for data cubes, featuring drag-and-drop exploration and AI agent integration.
  • lowreadme#3
    Add a 'Why Saiku?' or 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    ## Why Saiku?
Saiku stands out as an open-source solution specifically designed for exploring multidimensional OLAP cubes, particularly those powered by Mondrian. Unlike generic BI tools, Saiku provides a dedicated semantic layer with a typed REST API, enabling seamless integration with AI agents for data querying without requiring MDX knowledge. It offers a powerful drag-and-drop interface for business users while providing robust backend capabilities for developers.

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 spiculedata/saiku
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Tableau Desktop
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Tableau Desktop · recommended 1×
  2. Microsoft Power BI Desktop · recommended 1×
  3. Qlik Sense · recommended 1×
  4. Looker · recommended 1×
  5. Sisense · recommended 1×
  • CATEGORY QUERY
    How can I easily explore multidimensional data cubes with a drag-and-drop interface?
    you: not recommended
    AI recommended (in order):
    1. Tableau Desktop
    2. Microsoft Power BI Desktop
    3. Qlik Sense
    4. Looker
    5. Sisense
    6. Apache Superset (apache/superset)

    AI recommended 6 alternatives but never named spiculedata/saiku. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for an open-source semantic layer for data cubes with AI agent integration.
    you: not recommended
    AI recommended (in order):
    1. Cube.js
    2. Apache Superset
    3. Metabase
    4. Malloy
    5. dbt
    6. Apache Druid
    7. Apache Kylin

    AI recommended 7 alternatives but never named spiculedata/saiku. 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 spiculedata/saiku?
    pass
    AI named spiculedata/saiku explicitly

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

  • If a team adopts spiculedata/saiku in production, what risks or prerequisites should they evaluate first?
    pass
    AI named spiculedata/saiku 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 spiculedata/saiku solve, and who is the primary audience?
    pass
    AI named spiculedata/saiku 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 spiculedata/saiku. 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)
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HTML
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spiculedata/saiku — 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