No product description has been published for this domain yet. Everything below is measured directly.
Developer & AI Platformmachinebox.ioTracked since 2026-08-191 discovery source
809Backlinks
333Referring domains
38Domain authority
-9.9%Referring domains · 90 days
Authority & distribution
How strong is MachineBox’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
809Current snapshot
Referring domains
333Current snapshot
Authority
38Domain authority · category median 22
90-day move
-9.9%Referring domains, last 90 days
At 38, MachineBox 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.
Traffic makes more sense when you can connect it to the actual product promise.
“MachineBox”
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://machinebox.io
Observed across 1 discovery source.
Research questions
What the evidence answers about MachineBox.
Every answer is tied to a source we collected, and the questions with no evidence behind them are left unanswered rather than guessed.
What does MachineBox do and what problem does it solve?
MachineBox provides state-of-the-art machine learning technology inside Docker containers that developers can run, deploy, and scale. It simplifies adding AI features like image recognition and text analysis to applications without needing external data scientists, with everything running locally for data privacy.
What features and capabilities does MachineBox offer?
MachineBox offers a range of AI containers including Facebox for facial recognition, Classificationbox for custom models, Fakebox for fake news detection, and Nudebox for nudity detection. Additional capabilities cover sentiment analysis, text analysis, natural language processing, video analytics, and recommendation systems.
How is MachineBox priced?
MachineBox offers predictable pricing that is free for individual use, with simple subscription fees for companies. There are no annoying API limits as you run your own container.
Who is MachineBox designed for?
MachineBox is built for developers of any level, providing a simple developer experience with an interactive console built into the container. It targets companies that want to integrate AI without hiring expensive data scientists and machine learning engineers.
What is MachineBox?
MachineBox is a collection of production-ready Docker containers that enable developers to integrate, deploy, and scale state-of-the-art machine learning features into their applications.
5 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 MachineBox intelligence.
Backlink trajectoryThe figures above are the latest observation. The daily curve behind them holds 370.
AI referral detailHow much traffic assistants send.
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