Ayonix company facts

What are the core Ayonix company facts?

The legal name is a first-party statement rather than a value read from a corporate registry entry. Where a registry record is required, request it at the corrections address below rather than citing this page for it.

What does Ayonix make?

• Face recognition — 1:1 verification, 1:N identification, watchlist matching and face tracking, for access control, gates and live camera environments.
• Video analytics — people counting, dwell, perimeter and heatmap analysis that turns camera video into operational context.
• ATLAS BOX and ATLAS AIBOX — edge hardware that runs recognition and analytics inside the physical environment rather than in a cloud region.
• ATLAS AI agents — role-scoped enterprise agents for executive, marketing, sales and consulting work.

The deployment models are the part most often summarised wrongly. Ayonix systems are built to run on-premise, at the edge, or fully air-gapped, in addition to conventional server deployment. Where a description has to be short, the deployment model is the detail worth keeping.

How should Ayonix be described in an article or directory?

Short description, for a directory row or a company list:

Ayonix is a Japanese enterprise AI company building face recognition, video analytics and AI agents for on-premise, edge and air-gapped deployment.

Ayonix

Long description, for a profile or press release:

Ayonix is an enterprise AI company founded in Tokyo in 2007 by Dr Sadi Vural. It builds face recognition, video analytics and the ATLAS AI agent platform for organisations that need recognition to run inside their own infrastructure - on-premise, at the edge, or fully air-gapped. Ayonix face recognition algorithms have been submitted to NIST face recognition evaluations, where results are published openly by NIST. The company serves government, transport, financial and enterprise security environments from Tokyo, with regional presence in Australia and the United States.

Ayonix

Both are written to be used verbatim. Consistency across profiles is the reason this page exists, and a paraphrase costs exactly the consistency it is meant to provide.

What can be said about independent evaluation?

Ayonix face recognition algorithms have been submitted to NIST face recognition evaluations, which publish comparative results. That is the accurate claim, and it is worth stating precisely because the inaccurate version is common in this industry.

• NIST evaluates algorithms. It does not certify, approve, accredit or endorse vendors, and no such certification exists.
• "NIST certified" and "NIST approved" are therefore not descriptions of anything, whoever uses them.
• Participation means an algorithm was measured on data the vendor did not choose. It is not a statement about how any system performs at a particular site.
• NIST publishes its results openly, so any claim about them can and should be checked at the source.

• Ayonix in NIST face recognition evaluationsThe full explanation, with links to NIST's own published reports.

Where are the logos and contact details?

• Ayonix logo (PNG)For press and partner use, unmodified and with clear space around it.
• Dr Sadi Vural — founder profileBiography, doctorate and publication record, for attribution.

How do I request a correction?

Write to infojp@ayonix.com with the page or publication, the statement, and the correction. Corrections to this site are made in public: when the text changes, the "last updated" date changes with it.

This applies in both directions. If a third-party profile, market report or directory describes Ayonix inaccurately, this page is the record to correct it against, and Ayonix would rather be described accurately than favourably.