The Index data ledger

Vendor recommendation presence in a disclosed multi-client agency-owner prompt context.

Vendor recommendation presence in a disclosed in-house SEO and AEO lead prompt context.

Vendor recommendation presence when every buying prompt explicitly asks for the Australian market.

Vendor recommendation presence when every buying prompt explicitly asks for the Canadian market.

Vendor recommendation presence when every buying prompt explicitly asks for the United Kingdom market.

Vendor recommendation presence when every buying prompt explicitly asks for the United States market.

Reviewed AEO and AI-search analytics vendors ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

How often three model APIs name or cite each model and API platform when asked a fixed, public set of buying questions.

Domains ranked by unique cited answers, prompt breadth, engine breadth, and position.

The pages AI answers cite most across the public buying questions, ranked by the share of answers that cite them.

Reviewed brands ranked by the share of all the category's answers that name or cite them.

Reviewed brands ranked by answer-level citations to their reviewed domains.

Reviewed brands ranked by how many of the three model APIs name or cite them.

The brand named most for each public buying question, and how many of the three model APIs agree.

Prompts ranked by mean pairwise Jaccard distance between the reviewed-brand sets surfaced by each engine.

Prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Buying questions ranked by how much their answers moved since the previous snapshot: a new leader, or a shift in how far the model APIs agree.

Reviewed brands ranked by how often OpenAI's model API names or cites them in answers to the category's recommendation questions.

Reviewed brands ranked by how often Anthropic's model API names or cites them in answers to the category's recommendation questions.

Reviewed brands ranked by how often Google's Gemini model API names or cites them in answers to the category's recommendation questions.

Vendor recommendation presence in a disclosed small-team founder prompt context.

Vendor recommendation presence in a disclosed enterprise VP of marketing prompt context.

Hugging Face repository downloads and engagement for a fixed, reviewed model cohort.

Official style-controlled text human-preference ratings with confidence bounds, variance, vote counts, and a frozen dataset revision.

Exact model configurations ranked by the latest official LiveBench release: one benchmark's view of capability.

Official cost per successful LiveBench task beside capability, token use, and the exact prices frozen into the release.

Exact model-plus-inference configurations ranked by UC Berkeley BFCL V4 overall accuracy, with tool-use breakdowns, cost, latency, and source evidence.

Hourly Akash Network median and minimum GPU-hour prices, available units, total supply, provider count, memory, and interface.

Reviewed first-party project announcements ranked by disclosed reference amount, with qualifiers preserved and actual spend explicitly separated.

A reviewed first-party project cohort with announced, under-construction, and energized stages plus separately scoped disclosed datacenter and compute MW. Permits and grid queues are never inferred.

Exact public Linux on-demand EC2 prices in US East (N. Virginia), normalized by documented physical GPU count.

Announced and permitted capacity separated by development stage and confidence.

Epoch AI current positive-capacity facilities ranked by estimated total facility MW, with 2025-dollar capex and calculated H100-equivalent compute beside every row.

Latest future-dated Epoch AI capacity milestone per facility, with planned MW, 2025-dollar capex, H100e, construction status, evidence, and uncertainty preserved.

Reviewed cloud platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed providers ranked by the share of all the category's answers that name or cite them.

Reviewed providers ranked by distinct answer-level citations to their canonical domains.

Reviewed providers ranked by how many of the three model APIs name or cite them.

The provider named most for each cloud buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each provider is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each provider is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each provider is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed GPU infrastructure providers ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed providers ranked by the share of all the category's answers that name or cite them.

Reviewed providers ranked by distinct answer-level citations to their canonical domains.

Reviewed providers ranked by how many of the three model APIs name or cite them.

The provider named most for each infrastructure buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each provider is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each provider is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each provider is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed vector retrieval platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed platforms ranked by the share of all the category's answers that name or cite them.

Reviewed platforms ranked by distinct answer-level citations to their canonical domains.

Reviewed platforms ranked by how many of the three model APIs name or cite them.

The platform named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each platform is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each platform is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each platform is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Statewide average retail electricity prices for commercial and industrial customers, from EIA.

Exact Linux on-demand Azure West US 3 VM and normalized physical GPU-hour retail prices for a fixed reviewed SKU cohort.

First-party reported accelerator memory capacity and bandwidth for a fixed reviewed NVIDIA and AMD cohort.

Epoch AI estimates of the compute each company owns, in H100 equivalents, with uncertainty bands and chip context. It counts hardware owned; how much of it runs is a separate question.

EPA eGRID generation-based annual state CO2e output rates with nameplate capacity, net generation, and coal, gas, nuclear, and renewable mix. Not consumption-based, marginal, or data-center-specific.

Reported revenue, assets, CapEx, cash, and attributable AI-cloud revenue with raw values and source periods.

Latest reported fiscal-year capital expenditure.

Who produces chips, models, clouds, applications, and datacenter capacity.

SEC-reported total-company TTM CapEx divided by TTM revenue, with latest-quarter CapEx, debt, exact filing evidence, and incomplete issuers excluded.

Cumulative closed primary equity funding from Epoch AI. Debt, secondary sales, discussions, cancelled rounds, and valuations are excluded.

Latest full-company annualized revenue values from Epoch AI, with ARR versus other bases, evidence class, confidence, and source date preserved.

Companies ordered by disclosed forward capital expenditure.

Latest Epoch AI records explicitly scoped to the full company; division, role, contractor, and missing-scope values remain outside the leaderboard.

Latest publishable annual compute-spend evidence from Epoch AI, with totals separated from derived inference-plus-R&D component sums and never labeled CapEx.

The public companies financing the AI build-out, ranked by long-term debt relative to total assets, from company filings.

Reviewed AI tracing and evaluation platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed platforms ranked by the share of all the category's answers that name or cite them.

Reviewed platforms ranked by distinct answer-level citations to their canonical domains.

Reviewed platforms ranked by how many of the three model APIs name or cite them.

The platform named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each platform is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each platform is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each platform is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Institutions ranked by field-normalized output and citation impact.

Trailing-365-day OpenAlex-indexed AI works by authorship country, with the exact all-work denominator, unknown geography, and multinational counting disclosed.

OpenAlex-indexed AI works and citation signals for a fixed, reviewed lab and institution cohort.

Reviewed AI customer agent platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

Buying questions where the model APIs name the leading vendor but do not cite its own website.

Buying questions ranked by how much their answers moved since the previous snapshot: a new leader, or a shift in how far the model APIs agree.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

The pages AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed clinical AI documentation platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

Buying questions where the model APIs name the leading vendor but do not cite its own website.

Buying questions ranked by how much their answers moved since the previous snapshot: a new leader, or a shift in how far the model APIs agree.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

The pages AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed legal AI platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

Buying questions where the model APIs name the leading vendor but do not cite its own website.

Buying questions ranked by how much their answers moved since the previous snapshot: a new leader, or a shift in how far the model APIs agree.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

The pages AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed AI voice and audio platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

Buying questions where the model APIs name the leading vendor but do not cite its own website.

Buying questions ranked by how much their answers moved since the previous snapshot: a new leader, or a shift in how far the model APIs agree.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

The pages AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed AI video generation platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

Buying questions where the model APIs name the leading vendor but do not cite its own website.

Buying questions ranked by how much their answers moved since the previous snapshot: a new leader, or a shift in how far the model APIs agree.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

The pages AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed AI image generation platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

Buying questions where the model APIs name the leading vendor but do not cite its own website.

Buying questions ranked by how much their answers moved since the previous snapshot: a new leader, or a shift in how far the model APIs agree.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

The pages AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed AI writing and content platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

Buying questions where the model APIs name the leading vendor but do not cite its own website.

Buying questions ranked by how much their answers moved since the previous snapshot: a new leader, or a shift in how far the model APIs agree.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

The pages AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed AI research assistants ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

Buying questions where the model APIs name the leading vendor but do not cite its own website.

Buying questions ranked by how much their answers moved since the previous snapshot: a new leader, or a shift in how far the model APIs agree.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

The pages AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed AI meeting assistants ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

Buying questions where the model APIs name the leading vendor but do not cite its own website.

Buying questions ranked by how much their answers moved since the previous snapshot: a new leader, or a shift in how far the model APIs agree.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

The pages AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed commerce platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each commerce buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed creative platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each creative buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed workplace platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each workplace buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed finance platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each finance buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed workforce platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each workforce buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed revenue-data platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each revenue data buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed marketing platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each marketing buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed service platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each service buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed analytics platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each analytics buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed integration platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each integration buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed data platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each data platform buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed CRM vendors ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each CRM buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed security vendors ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed vendors ranked by the share of all the category's answers that name or cite them.

Reviewed vendors ranked by their share of the citations that point to vendor websites.

Reviewed vendors ranked by how many of the three model APIs name or cite them.

The vendor named most for each security buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each vendor is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each vendor is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed coding tools ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed tools ranked by the share of all the category's answers that name or cite them.

Reviewed tools ranked by distinct answer-level citations to their canonical domains.

Reviewed tools ranked by how many of the three model APIs name or cite them.

The tool named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each tool is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each tool is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each tool is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed enterprise search and retrieval platforms ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed platforms ranked by the share of all the category's answers that name or cite them.

Reviewed platforms ranked by distinct answer-level citations to their canonical domains.

Reviewed platforms ranked by how many of the three model APIs name or cite them.

The platform named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each platform is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each platform is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each platform is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Reviewed agent frameworks ranked by how often answers to the category's recommendation questions name or cite them, across three model APIs.

Reviewed frameworks ranked by the share of all the category's answers that name or cite them.

Reviewed frameworks ranked by distinct answer-level citations to their canonical domains.

Reviewed frameworks ranked by how many of the three model APIs name or cite them.

The framework named most for each buying question, and how many of the three model APIs agree.

Buying questions ranked by how differently the three model APIs answer them.

The websites AI answers cite most for the category's buying questions, ranked by the share of answers that cite them.

How often each framework is named or cited in OpenAI's model API answers to the category's recommendation questions.

How often each framework is named or cited in Anthropic's model API answers to the category's recommendation questions.

How often each framework is named or cited in Google's Gemini model API answers to the category's recommendation questions.

Net trailing-365-day federal transaction obligations by recipient using an exact AI phrase, NAICS, and PSC contract; potential award value is excluded.

The same qualifying USAspending transactions grouped by exact awarding-agency name, with obligations and deobligations included and potential award value excluded.

Exact npm downloads and separate GitHub activity for a fixed reviewed cohort of agent frameworks, agent SDKs, and MCP tools.

Hugging Face downloads, likes and repository recency for a fixed, reviewed set of datasets: a measure of activity on the platform.

Stars, forks, open work, and repository freshness for a fixed, reviewed AI-tooling cohort.

Exact BLS SOC 15-2051 state employment ranked with concentration, annual pay, survey error, and suppression status preserved.

Latest closed-round post-money valuation reported by Epoch AI for each covered company, with transaction scope and evidence.

Ranks LLM Observability prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks reviewed AI Visibility · Agency Owner brands by the share of all successful benchmark answers in which they appear.

Ranks reviewed AI Visibility · Agency Owner brands by their share of answer-level citations to reviewed brand domains.

Ranks reviewed AI Visibility · Agency Owner brands by the number of benchmark engines on which they appear.

Shows the leading reviewed AI Visibility · Agency Owner brand for every public prompt and its cross-engine consistency.

Ranks AI Visibility · Agency Owner prompts by how differently the configured engines surface the reviewed brand universe.

Ranks AI Visibility · Agency Owner prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Domains ranked by unique cited-answer coverage across Rank.ai's complete public prompt benchmark. This measures sourcing visibility—not recommendation or authority.

Ranks reviewed AI Visibility · Agency Owner brands by presence in OpenAI's configured model API answers to the fixed public prompt cohort. This does not measure the consumer application.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks reviewed AI Visibility · Agency Owner brands by presence in Anthropic's configured model API answers to the fixed public prompt cohort. This does not measure the consumer application.

Ranks reviewed AI Visibility · Agency Owner brands by presence in Gemini's configured model API answers to the fixed public prompt cohort. This does not measure the consumer application.

Ranks reviewed AI Visibility · In-house SEO/AEO Lead brands by the share of all successful benchmark answers in which they appear.

Ranks reviewed AI Visibility · In-house SEO/AEO Lead brands by their share of answer-level citations to reviewed brand domains.

Ranks reviewed AI Visibility · In-house SEO/AEO Lead brands by the number of benchmark engines on which they appear.

Shows the leading reviewed AI Visibility · In-house SEO/AEO Lead brand for every public prompt and its cross-engine consistency.

Ranks AI Visibility · In-house SEO/AEO Lead prompts by how differently the configured engines surface the reviewed brand universe.

Ranks AI Visibility · In-house SEO/AEO Lead prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Domains ranked by unique cited-answer coverage across Rank.ai's complete public prompt benchmark. This measures sourcing visibility—not recommendation or authority.

Ranks reviewed AI Visibility · In-house SEO/AEO Lead brands by presence in OpenAI's configured model API answers to the fixed public prompt cohort. This does not measure the consumer application.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks reviewed AI Visibility · In-house SEO/AEO Lead brands by presence in Anthropic's configured model API answers to the fixed public prompt cohort. This does not measure the consumer application.

Ranks reviewed AI Visibility · In-house SEO/AEO Lead brands by presence in Gemini's configured model API answers to the fixed public prompt cohort. This does not measure the consumer application.

Ranks reviewed AI Visibility · Australia brands by the share of all successful benchmark answers in which they appear.

Ranks reviewed AI Visibility · Australia brands by their share of answer-level citations to reviewed brand domains.

Ranks reviewed AI Visibility · Australia brands by the number of benchmark engines on which they appear.

Shows the leading reviewed AI Visibility · Australia brand for every public prompt and its cross-engine consistency.

Ranks AI Visibility · Australia prompts by how differently the configured engines surface the reviewed brand universe.

Ranks AI Visibility · Australia prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Domains ranked by unique cited-answer coverage across Rank.ai's complete public prompt benchmark. This measures sourcing visibility—not recommendation or authority.

Ranks reviewed AI Visibility · Australia brands by presence in OpenAI's configured model API answers to the fixed public prompt cohort. This does not measure the consumer application.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks reviewed AI Visibility · Australia brands by presence in Anthropic's configured model API answers to the fixed public prompt cohort. This does not measure the consumer application.

Ranks reviewed AI Visibility · Australia brands by presence in Gemini's configured model API answers to the fixed public prompt cohort. This does not measure the consumer application.

Ranks reviewed AI Visibility · Canada brands by the share of all successful benchmark answers in which they appear.

Ranks reviewed AI Visibility · Canada brands by their share of answer-level citations to reviewed brand domains.

Ranks reviewed AI Visibility · Canada brands by the number of benchmark engines on which they appear.

Shows the leading reviewed AI Visibility · Canada brand for every public prompt and its cross-engine consistency.

Ranks AI Visibility · Canada prompts by how differently the configured engines surface the reviewed brand universe.

Ranks AI Visibility · Canada prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Domains ranked by unique cited-answer coverage across Rank.ai's complete public prompt benchmark. This measures sourcing visibility—not recommendation or authority.

Ranks reviewed AI Visibility · Canada brands by presence in OpenAI's configured model API answers to the fixed public prompt cohort. This does not measure the consumer application.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks reviewed AI Visibility · Canada brands by presence in Anthropic's configured model API answers to the fixed public prompt cohort. This does not measure the consumer application.

Ranks reviewed AI Visibility · Canada brands by presence in Gemini's configured model API answers to the fixed public prompt cohort. This does not measure the consumer application.

Ranks reviewed AI Visibility · United Kingdom brands by the share of all successful benchmark answers in which they appear.

Ranks reviewed AI Visibility · United Kingdom brands by their share of answer-level citations to reviewed brand domains.

Ranks reviewed AI Visibility · United Kingdom brands by the number of benchmark engines on which they appear.

Shows the leading reviewed AI Visibility · United Kingdom brand for every public prompt and its cross-engine consistency.

Ranks AI Visibility · United Kingdom prompts by how differently the configured engines surface the reviewed brand universe.

Ranks AI Visibility · United Kingdom prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Domains ranked by unique cited-answer coverage across Rank.ai's complete public prompt benchmark. This measures sourcing visibility—not recommendation or authority.

Ranks reviewed AI Visibility · United Kingdom brands by presence in OpenAI's configured model API answers to the fixed public prompt cohort. This does not measure the consumer application.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks reviewed AI Visibility · United Kingdom brands by presence in Anthropic's configured model API answers to the fixed public prompt cohort. This does not measure the consumer application.

Ranks reviewed AI Visibility · United Kingdom brands by presence in Gemini's configured model API answers to the fixed public prompt cohort. This does not measure the consumer application.

Ranks reviewed AI Visibility · United States brands by the share of all successful benchmark answers in which they appear.

Ranks reviewed AI Visibility · United States brands by their share of answer-level citations to reviewed brand domains.

Ranks reviewed AI Visibility · United States brands by the number of benchmark engines on which they appear.

Shows the leading reviewed AI Visibility · United States brand for every public prompt and its cross-engine consistency.

Ranks AI Visibility · United States prompts by how differently the configured engines surface the reviewed brand universe.

Ranks AI Visibility · United States prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Domains ranked by unique cited-answer coverage across Rank.ai's complete public prompt benchmark. This measures sourcing visibility—not recommendation or authority.

Ranks reviewed AI Visibility · United States brands by presence in OpenAI's configured model API answers to the fixed public prompt cohort. This does not measure the consumer application.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks reviewed AI Visibility · United States brands by presence in Anthropic's configured model API answers to the fixed public prompt cohort. This does not measure the consumer application.

Ranks reviewed AI Visibility · United States brands by presence in Gemini's configured model API answers to the fixed public prompt cohort. This does not measure the consumer application.

Ranks Commerce Platforms prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Latest reported daily token throughput in Epoch AI for each covered company, retaining product scope and source evidence.

Ranks Design & Creative prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks Collaboration prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks Finance & ERP prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks HR & Recruiting prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks Sales Intelligence prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks Marketing Automation prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks Customer Support prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks BI & Analytics prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks Data Integration prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks Cloud Platforms prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks Data Platforms prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks CRM Platforms prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks Cybersecurity Platforms prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks Cloud GPU Platforms prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks AI Developer Tools prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks Enterprise Search prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks Agent Frameworks prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Ranks Vector Databases prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks AI Visibility Platforms prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks reviewed AI Visibility · Startup Founder brands by the share of all successful benchmark answers in which they appear.

Ranks reviewed AI Visibility · Startup Founder brands by their share of answer-level citations to reviewed brand domains.

Ranks reviewed AI Visibility · Startup Founder brands by the number of benchmark engines on which they appear.

Shows the leading reviewed AI Visibility · Startup Founder brand for every public prompt and its cross-engine consistency.

Ranks AI Visibility · Startup Founder prompts by how differently the configured engines surface the reviewed brand universe.

Ranks AI Visibility · Startup Founder prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Reviewed prompts ranked by changed leaders and movement in cross-engine consensus and disagreement.

Domains ranked by unique cited-answer coverage across Rank.ai's complete public prompt benchmark. This measures sourcing visibility—not recommendation or authority.

Ranks reviewed AI Visibility · Startup Founder brands by presence in OpenAI's configured model API answers to the fixed public prompt cohort. This does not measure the consumer application.

Canonical pages ranked by complete-cohort cited-answer coverage, engine breadth, prompt breadth, and citation position. This measures sourcing visibility—not authority.

Ranks reviewed AI Visibility · Startup Founder brands by presence in Anthropic's configured model API answers to the fixed public prompt cohort. This does not measure the consumer application.

Ranks reviewed AI Visibility · Startup Founder brands by presence in Gemini's configured model API answers to the fixed public prompt cohort. This does not measure the consumer application.

Ranks reviewed AI Visibility · Enterprise Marketing Leader brands by the share of all successful benchmark answers in which they appear.

Ranks reviewed AI Visibility · Enterprise Marketing Leader brands by their share of answer-level citations to reviewed brand domains.

Ranks reviewed AI Visibility · Enterprise Marketing Leader brands by the number of benchmark engines on which they appear.

Shows the leading reviewed AI Visibility · Enterprise Marketing Leader brand for every public prompt and its cross-engine consistency.

Ranks AI Visibility · Enterprise Marketing Leader prompts by how differently the configured engines surface the reviewed brand universe.

Ranks AI Visibility · Enterprise Marketing Leader prompts where the leading reviewed brand appears across engines but its own domains are not cited.

Domains ranked by unique cited-answer coverage across Rank.ai's complete public prompt benchmark. This measures sourcing visibility—not recommendation or authority.

Ranks reviewed AI Visibility · Enterprise Marketing Leader brands by presence in OpenAI's configured model API answers to the fixed public prompt cohort. This does not measure the consumer application.

Ranks reviewed AI Visibility · Enterprise Marketing Leader brands by presence in Anthropic's configured model API answers to the fixed public prompt cohort. This does not measure the consumer application.

Ranks reviewed AI Visibility · Enterprise Marketing Leader brands by presence in Gemini's configured model API answers to the fixed public prompt cohort. This does not measure the consumer application.

Exact trailing npm download signals for a reviewed cohort of public JavaScript AI SDKs and frameworks.