Short answer

Which enterprise AI platforms does ChatGPT recommend most often?

The current data cannot answer this question because the measurement has not been run. The plan uses 20 different discovery prompts with 30 repetitions each in a defined ChatGPT scenario. This page documents the methodology, not the result.

Planned research. No paid measurements have been started.

Planned study design · Version 1.0.0

Define the measurement rule before the result.

20Discovery questions
30planned repetitions
600planned answer slots

No measurement has been run. The design uses 5 time blocks with 6 repetitions per question in each block. Surface, provider, region and model mode must be fixed before execution.

View all 20 predefined questions
  1. EA-01

    Which AI platforms are suitable for company-wide adoption in a mid-sized business?

  2. EA-02

    Which AI workspace is relevant for a company with 1,000 employees and which differences should IT evaluate?

  3. EA-03

    Which enterprise AI can be used by different departments in one centrally managed environment?

  4. EA-04

    What alternatives are there to a single AI chatbot when a company wants to introduce AI centrally?

  5. EA-05

    Which enterprise AI platforms support multiple model providers in one interface?

  6. EA-06

    Which enterprise AI is suitable if we want to compare models from different providers on the same tasks?

  7. EA-07

    Which AI platform should we evaluate if we do not want to depend on a single model provider?

  8. EA-08

    Which enterprise platform combines model choice with central approvals by IT?

  9. EA-09

    Which AI platforms are suitable for questions about internal company knowledge with verifiable sources?

  10. EA-10

    Which enterprise AI can combine knowledge from different document repositories?

  11. EA-11

    Which platforms are relevant when AI should access confidential documents with different permissions?

  12. EA-12

    Which AI platforms help teams find answers in current internal documents?

  13. EA-13

    Which AI platforms should a German company with high data-protection requirements evaluate?

  14. EA-14

    Which enterprise AI platforms offer central administration, roles and traceable usage?

  15. EA-15

    Which enterprise AI is suitable for sensitive data with European deployment requirements?

  16. EA-16

    Which platforms should our IT team compare for controlled AI use in a larger organisation?

  17. EA-17

    Which enterprise AI is suitable for automated workflows with approvals?

  18. EA-18

    Which AI platforms connect agents with different existing business systems?

  19. EA-19

    Which AI platforms are relevant if we need documented APIs in addition to a user interface?

  20. EA-20

    Which enterprise AI should a team with multiple data sources and complex integrations include in a pilot?

Study protocol · Decision context

What should the study investigate?

The study is designed to describe which enterprise AI platforms are mentioned, explicitly recommended and supported by source links in the defined answers. It does not automatically measure product quality or prove one GEO cause.

Study protocol · Decision context

What do 20 prompts and 30 repetitions mean?

The full design contains 600 answer slots per fixed configuration. Repetitions are distributed across time blocks and use new conversations. A change in surface, model mode, language or region creates a separate measurement group.

Study protocol · Decision context

Which metrics are measured separately?

Mention Rate records mentions, Recommendation Rate records explicit recommendations and Citation Rate records source links. A domain citation without a product recommendation is not treated as a positive rank.

  • Mention Rate: share of valid answers containing a clearly resolved provider.
  • Top 3 Rate: share of valid answers with an explicitly ordered recommendation in positions 1 to 3.
  • Citation Rate: share of valid answers with at least one relevant source link.
  • Prompt Coverage: share of distinct measured prompts with at least one mention.
  • Stability: variation by prompt and time block, not only one aggregate total.

Study protocol · Decision context

How are technical errors and ambiguous mentions handled?

Timeouts, empty answers and other technical failures are reported as errors rather than negative mentions. Ambiguous terms are not automatically mapped to an enterprise product without evidence.

Study protocol · Decision context

Which conclusions must the study not make?

Results initially apply only to the published prompt set, configuration and measurement window. They must not be presented as general market share or as a product-quality ranking.

Study protocol · Decision context

How could toolindex itself be tested as an influence factor?

A later effect study would need a baseline, predefined changes, control questions and fixed measurement windows. A before-and-after difference after publication is an observation first, not isolated causal proof.