Building a Nationwide Centralized Facial Recognition System for Public Security Investigation

Following the 2015 G20 Antalya Summit deployment, Turkish security authorities needed to expand facial recognition capabilities from a mission-specific mobile system into a centralized platform that could support counter-terrorism units across Türkiye.

The objective was to enable authorized teams in all 81 provinces to search and analyze facial data from multiple sources, including archived images, seized media, video files, mobile field units and existing camera environments. The system needed to support high-volume investigation workflows, watchlist management, alarm review, auditability and controlled access for mission-critical public security operations.

Nevalabs provided Corvo Identify as the core facial recognition software layer for a centralized nationwide system used by the Turkish National Police – Counter Terrorism Department.

The centralized system received its official acceptance in December 2015 and continued with a multi-year operational support and improvement period through 2018. During this period, Nevalabs continued to work with Turkish National Police teams on operational refinements, software improvements and expanded investigation workflows.

The platform was designed with a 1,000,000-enrollment Corvo Identify license and supported facial recognition workflows from photos, archived images, video files, fixed camera deployments and mobile field units. The system included capabilities such as watchlist and organization management, photo-based search, video-based search, fixed camera-based recognition, mobile field recognition, alarm distribution, alarm verification, reporting, user activity and audit logs, role-based user authorization and LDAP integration.

As part of this phase, Nevalabs transitioned the facial recognition engine to a deep learning-based recognition architecture, significantly improving recognition performance compared to earlier-generation approaches. At the time, this represented a forward-looking implementation of deep learning-based facial recognition within a national security environment.

The project was developed through close collaboration with Turkish National Police counter-terrorism teams, with operational requirements translated into new software capabilities and investigation workflows. The system represented an important step in scaling facial recognition technology from high-security event protection into a centralized national investigation platform.

During a period marked by heightened national security risks, terrorist attacks and the July 15 coup attempt in Türkiye, the system supported authorized investigation teams by enabling facial recognition workflows from photos, videos, fixed cameras and mobile field units for public security operations.

Server and camera infrastructure were supplied through separate procurement processes, while Nevalabs delivered the facial recognition software layer.