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Which AI observability tools do AI engines actually recommend?

As of June 20, 2026, Datadog leads with a 17.7% share-of-model — it appears in 17.7% of all AI observability tools recommendations across 5 major AI engines.

See your product's share-of-model — free How we measured this

The leaderboard — AI observability tools by share-of-model

Which observability and monitoring platforms do AI engines recommend when developers and platform teams ask what to use? We ran 10 buyer prompts × 10 runs across 5 engines (Perplexity, Google Gemini, ChatGPT (OpenAI), Claude (Anthropic), Grok (xAI)) — 407 total AI answers. Last updated June 20, 2026.

Datadog leads our AI Visibility Index for AI observability tools at 18% share-of-model across 5 AI engines.

10 buyer prompts · 10 runs/engine · June 20, 2026Updated monthly
#ProductShare of modelSoM95% CIPerplexityGoogle GeminiChatGPT (OpenAI)Claude (Anthropic)Grok (xAI)
1Datadog datadoghq.com17.7%16.1%–19.5%71%100%85%85%96%
2New Relic newrelic.com14.9%13.4%–16.6%55%100%82%61%85%
3OpenTelemetry opentelemetry.io14.8%13.3%–16.4%52%100%72%72%84%
4Grafana grafana.com13.6%12.2%–15.2%57%100%67%55%78%
5Prometheus prometheus.io10.9%9.6%–12.4%46%100%63%29%67%
6Dynatrace dynatrace.com7.3%6.2%–8.5%31%0%32%32%46%
7Elastic elastic.co7.2%6.1%–8.5%23%29%39%20%56%
8Honeycomb honeycomb.io6.4%5.4%–7.6%28%43%31%19%43%
9Sentry sentry.io4.5%3.6%–5.5%21%0%16%26%24%
10Splunk splunk.com2.7%2.1%–3.5%27%0%5%6%14%

Share of model = % of all recommendations (across every prompt and engine) that named the product. Per-engine columns show how often each engine recommends the product. CI = Wilson 95% confidence interval on share-of-model.

Methodology — reproducible, not vibes

A single AI screenshot is one sample from a distribution. This Index treats AI visibility as the statistical question it is: every buyer prompt is run 10+ times per engine, and we report the median rate with a 95% confidence interval.

Buyer "money prompts"

10 real buyer questions a person would ask an AI when choosing AI observability tools (e.g. "best AI observability tools for a Series A startup"). Each prompt is run 10+ times per engine.

5 engines, measured separately

We query Perplexity, Google Gemini, ChatGPT (OpenAI), Claude (Anthropic), Grok (xAI) independently, because the engines disagree — being strong in one says nothing about the others. Per-engine columns expose that spread.

Share-of-model + Wilson CI

For each product we report its share of all recommendations in the field, with a 95% Wilson confidence interval — the honest way to summarize a small, noisy sample.

Heuristic detection, disclosed

A product is "recommended" when its name or a known alias is named in the answer (boundary-aware); a citation is counted when its own domain appears in the answer's sources. A mention is not always a positive endorsement — we say so.

API answers approximate, but do not exactly replicate, the consumer apps (different system prompts, tools, browsing defaults). We treat each edition as a point-in-time measurement and re-run on a cadence.

FAQ

Which AI observability tools do AI engines recommend most?

As of June 20, 2026, Datadog leads the Clear Cited AI Visibility Index for AI observability tools with a 17.7% share-of-model — meaning 17.7% of all product recommendations across 5 AI engines named it. See the full ranked table above.

What is share-of-model?

Share-of-model = the percentage of all product recommendations, across every buyer prompt and engine, that name a given product. It answers: when an AI recommends something in this category, how often is it this product?

How is the AI Visibility Index measured?

Each buyer prompt is run at least 10 times per engine across Perplexity, Google Gemini, ChatGPT (OpenAI), Claude (Anthropic), Grok (xAI). We detect which products each answer recommends, compute each product's share-of-model, and report a Wilson 95% confidence interval. The method is reproducible — the same one Clear Cited uses in its paid AI-visibility audits.

Why do different AI engines recommend different products?

AI answer engines draw on different training data, retrieval sources, and ranking — so the 'best tool' a buyer hears depends heavily on which assistant they ask. That is why the Index measures and reports each engine separately.

Is this ranking sponsored or pay-to-play?

No. The AI Visibility Index is free, independent original research. Products are not charged to appear and cannot pay to rank higher. It reflects what AI engines actually say, measured transparently.

Want your product's real share-of-model?

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