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Market/Categories/Developer & AI Platform/Ray

Independent product intelligence · Worldwide · 2026-05-01 → 2026-07-31

Rayray.io

No product description has been published for this domain yet. Everything below is measured directly.

Developer & AI Platformray.ioTracked since 2026-08-191 discovery source
33.3KBacklinks
3.7KReferring domains
35Domain authority
+5.2%Referring domains · 90 days

Authority & distribution

How strong is Ray’s web footprint?

Backlinks measure accumulated distribution; referring domains show how broadly that authority is spread. Both are observable on the open web, so both are published for every product here.

Backlinks

33.3KCurrent snapshot

Referring domains

3.7KCurrent snapshot

Authority

35Domain authority · category median 22

90-day move

+5.2%Referring domains, last 90 days
At 35, Ray sits above the 22 median for its category.

Trajectory · Pro

The counts above are the latest of 370 daily observations. The curve through them is on the full profile.

See the trajectoryOpen the full profile

Traffic & engagement

Where Ray ranks

Measured · Pro

Measured for this product: global rank, country rank and category rank.

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AI referral visibility

Which AI assistants are already sending Ray traffic?

Measured · Pro

Measured for this product: AI referral traffic, which assistants refer it and which pages those referrals land on.

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Product profile

What Ray is selling.

Traffic makes more sense when you can connect it to the actual product promise.

“Ray”

No usable description reached this profile from any discovery source, so none is shown. The measured signals below are unaffected.

Developer & AI PlatformSeen 2026-08-19 → 2026-08-19Coverage tier C

What we have measured

4 of 8 signal groups are available for this product: identity, authority and backlinks, AI referrals, search demand.

Not measured for this domain: traffic and engagement, audience demographics, country distribution, acquisition mix. Those sections are left out of the page rather than filled with estimates.

Canonical website: https://ray.io

Observed across 1 discovery source.

Research questions

What the evidence answers about Ray.

Every answer is tied to a source we collected, and the questions with no evidence behind them are left unanswered rather than guessed.

What are the main use cases and capabilities of Ray?

Ray is a Python-native framework that supports a wide range of AI and ML use cases. Its core capabilities include parallel Python code execution, multi-modal data processing (for images, videos, audio), distributed model training (including for Gen AI, time series, and traditional ML models), model serving with independent scaling (Ray Serve), batch inference with heterogeneous compute, and production-level reinforcement learning via RLlib. It can scale from a laptop to thousands of GPUs.

What is Ray and what problem does it solve?

Ray is an open-source AI compute engine designed to solve the 'AI Complexity Wall.' It provides a unified infrastructure to orchestrate, manage, and optimize compute needs for any distributed AI or ML workload, addressing issues like slow production time, underutilized resources, and high costs. It is built to handle any data type and model architecture across any accelerator at any scale.

Who is Ray designed for?

Ray is designed for developers and teams building and scaling machine learning and AI applications. It is described as being 'built by developers for developers' and serves as the core compute engine for complex AI platforms that require efficient infrastructure for distributed workloads.

3 of 6 research questions are answered for this product. The rest need source evidence we have not collected yet, so they are left unanswered rather than guessed.

Behind the lock

Unlock full Ray intelligence.

  • Backlink trajectoryThe figures above are the latest observation. The daily curve behind them holds 370.
  • AI referral detailHow much traffic assistants send, which 6 of them do it, and the 24 pages they land on.
  • Search structure and ranking depthOrganic against paid, brand against non-brand, and how many keywords rank in the top three against the long tail — which is what decides whether the demand is portable or tied to the name.
  • The rest of the marketPage through every leaderboard 100 rows at a time, put any five products side by side, and query the whole dataset over API / MCP.

Worldwide estimates · Data period 2026-05-01 → 2026-07-31. Figures are measured estimates intended for market research. Signals we have not measured for this domain are omitted, never estimated; a measured zero is still reported as zero. How this was measured