https://facerec.ayonix.com Enterprise face recognition for access control, airport eGates, border checkpoints and watchlist monitoring. On-premise, edge and air-gapped deployment. en © 2026 Ayonix Wed, 16 Sep 2026 02:51:49 GMT https://facerec.ayonix.com/solutions https://facerec.ayonix.com/solutions Nine solution pages covering the four environments face recognition is deployed into — access control, airport eGates, border checkpoints and watchlist monitoring — plus the two architectures that decide the rest of the design, on-premise and edge, and three video management system integrations. Fri, 11 Sep 2026 00:00:00 GMT https://facerec.ayonix.com/solutions/face-recognition-access-control https://facerec.ayonix.com/solutions/face-recognition-access-control Face recognition access control identifies an enrolled person at a door using 1:N matching against a managed gallery, then sends an open command to the door controller. It removes cards, shortens queues at entrances, and records every decision including refusals for audit. Fri, 11 Sep 2026 00:00:00 GMT https://facerec.ayonix.com/solutions/airport-egate-face-verification https://facerec.ayonix.com/solutions/airport-egate-face-verification Airport eGate face verification compares the portrait read from a traveller’s document by the authorised reader against the face captured at the gate. It is a 1:1 verification problem, not identification, and its job is to send the officer the exceptions rather than the queue. Fri, 11 Sep 2026 00:00:00 GMT https://facerec.ayonix.com/solutions/border-control-face-recognition https://facerec.ayonix.com/solutions/border-control-face-recognition Border control face recognition covers two distinct operations: 1:1 verification of a traveller against their document at the checkpoint, and authorised 1:N search against segmented identity records. Both must work across sites that may have no connectivity, and both require human review before consequential action. Fri, 11 Sep 2026 00:00:00 GMT https://facerec.ayonix.com/solutions/watchlist-face-recognition https://facerec.ayonix.com/solutions/watchlist-face-recognition Watchlist face recognition compares faces detected in live camera streams against a managed, authorised list and raises an alert for an operator to review. The design problem is not detection but alert volume: quality gating, tracking and threshold policy decide whether operators trust the system. Fri, 11 Sep 2026 00:00:00 GMT https://facerec.ayonix.com/solutions/on-premise-face-recognition https://facerec.ayonix.com/solutions/on-premise-face-recognition On-premise face recognition runs matching on servers inside the customer’s own network, so face images and biometric templates never leave the premises. It removes internet round-trip latency and recurring per-transaction cost, and puts retention, access control and audit under systems the customer already operates. Fri, 11 Sep 2026 00:00:00 GMT https://facerec.ayonix.com/solutions/edge-face-recognition https://facerec.ayonix.com/solutions/edge-face-recognition Edge face recognition processes video on an appliance beside the cameras and transmits only events, not streams. It gives the lowest decision latency of any architecture, keeps a site working while its WAN link is down, and removes the bandwidth cost of backhauling video that is never watched. Fri, 11 Sep 2026 00:00:00 GMT https://facerec.ayonix.com/technology https://facerec.ayonix.com/technology How Ayonix face recognition is evaluated, what independent evidence exists, how liveness is tested against named attack instruments, and what governance a deployment needs. Every external claim links to its primary source; no accuracy percentage appears anywhere on this site. Fri, 11 Sep 2026 00:00:00 GMT https://facerec.ayonix.com/technology/nist-evaluation https://facerec.ayonix.com/technology/nist-evaluation Ayonix algorithms have been submitted to NIST face recognition evaluations in both the 1:1 verification and 1:N identification tracks. NIST publishes comparative results and does not certify or endorse vendors — no NIST certification exists. This page links NIST’s own records rather than summarising them. Fri, 11 Sep 2026 00:00:00 GMT https://facerec.ayonix.com/technology/accuracy-and-testing https://facerec.ayonix.com/technology/accuracy-and-testing Ayonix publishes no accuracy percentage, because a figure without its threshold, dataset, gallery size and demographic breakdown cannot be reproduced. Accuracy for a deployment is established by a pilot on the site’s own cameras, measuring both error types and reporting where the threshold was left. Fri, 11 Sep 2026 00:00:00 GMT https://facerec.ayonix.com/technology/liveness-and-presentation-attack-detection https://facerec.ayonix.com/technology/liveness-and-presentation-attack-detection Liveness detection assesses whether a presented face comes from a live person rather than a photograph, screen replay or mask. A liveness claim means nothing without the attack instruments it was tested against, who tested it and when — the reporting framework ISO/IEC 30107-3 defines. Fri, 11 Sep 2026 00:00:00 GMT https://facerec.ayonix.com/technology/privacy-and-governance https://facerec.ayonix.com/technology/privacy-and-governance Responsible face recognition needs a purpose narrow enough to test, retention short enough to survive audit, human review that is a real control rather than a signature, and a fallback path that does not single people out. This page sets out the controls a deployment should carry. Fri, 11 Sep 2026 00:00:00 GMT https://facerec.ayonix.com/evidence https://facerec.ayonix.com/evidence Every claim this site makes, with the source that supports it and what it does not establish. Claims are registered before they may be published, and the build fails if a page states one it is not approved for. Rejected claims are listed with the reason. Fri, 11 Sep 2026 00:00:00 GMT https://facerec.ayonix.com/case-studies https://facerec.ayonix.com/case-studies Two deployments Ayonix is authorised to publish: a United Nations border-control project across more than 20 cameras, and ITOCHU Techno-Solutions replacing RFID office access cards with Ayonix FaceID. No unnamed customer, invented metric or unapproved deployment appears here. Fri, 11 Sep 2026 00:00:00 GMT https://facerec.ayonix.com/resources https://facerec.ayonix.com/resources Practical documents for people specifying a system: a camera planning guide covering the geometry that decides whether recognition works at all, and a pilot checklist setting out the acceptance criteria to agree before any vendor arrives on site. Fri, 11 Sep 2026 00:00:00 GMT https://facerec.ayonix.com/resources/camera-planning-guide https://facerec.ayonix.com/resources/camera-planning-guide Face recognition succeeds or fails on capture geometry: pixels across the eyes at the point people actually pass, mounting height and angle, standoff distance, lighting direction and subject movement. This guide covers each, and what good placement still cannot fix. Fri, 11 Sep 2026 00:00:00 GMT https://facerec.ayonix.com/resources/face-recognition-pilot-checklist https://facerec.ayonix.com/resources/face-recognition-pilot-checklist What to agree before a vendor arrives: the population, the measurement window, how many subjects a result actually needs, both error types to record, the threshold and who may change it, and how the outcome is reported. Written to be used against Ayonix as well as by it. Fri, 11 Sep 2026 00:00:00 GMT https://facerec.ayonix.com/compare/enterprise-face-recognition-software https://facerec.ayonix.com/compare/enterprise-face-recognition-software A comparison of the five categories of face recognition system — cloud API, device-only terminal, identity-verification service, on-premise platform and edge appliance — against the requirements that actually decide the choice. Ayonix publishes it and appears in it; that is stated on the page. Fri, 11 Sep 2026 00:00:00 GMT https://facerec.ayonix.com/case-studies/itochu-techno-solutions-office-access https://facerec.ayonix.com/case-studies/itochu-techno-solutions-office-access ITOCHU Techno-Solutions adopted Ayonix FaceID across its offices in 2016, using iPads as facial-authentication terminals to replace RFID access cards. Fri, 11 Sep 2026 00:00:00 GMT https://facerec.ayonix.com/case-studies/united-nations-border-control https://facerec.ayonix.com/case-studies/united-nations-border-control Ayonix face recognition across more than 20 border-gate cameras for a United Nations border-control project, supporting identity verification and passport control. Fri, 11 Sep 2026 00:00:00 GMT