TECH5 Demonstrates a New Balance of Accuracy, Speed and Efficiency in NIST IREX 10
Digital Government Africa 2027
TECH5, Visa, and Presight will jointly participate in the ID4Africa 2026 Annual General Meeting (AGM) and exhibition.
ID4Africa 2026
TECH5, Visa, and Presight will jointly participate in the ID4Africa 2026 Annual General Meeting (AGM) and exhibition.
TechMag and TECH5 will Participate in FEBRABAN SEC 2026
TECH5 Sets a New Global Benchmark in Biometric Identification Speed and Accuracy
Febraban SEC 2026
DPI to Become One of the Main Drivers for Government Digital Ecosystems in 2026
MOSIP Connect 2026
TECH5 Receives Multi-Million Euro Growth Funding from Salica Investments
Honduras Launches National Digital ID and Trust Framework on TECH5’s DPI Platform, Setting a Replicable Model for Latin America
Papua New Guinea Launches National Digital ID and Identity Wallet Powered by TECH5’s DPI Platform, Making it the First Decentralized Digital Public Infrastructure Ecosystem in Oceania
CITEC 2025
TECH5 and AJARI Partner to Integrate Conversational AI into the Next Generation DPI
Decentralized Digital Public Infrastructure: Why Governments Must Look Ahead
NIST One-To-Many (FRIF TE E1N) Evaluation: How it Works and Why it is Important
Friction Ridge Image and Features (FRIF) Technology Evaluation (TE) Exemplar One-to-Many (E1N), or FRIF TE E1N, is a new open-set identification evaluation of algorithms launched in 2025 that automatically extract and use features from all types of exemplar friction ridge images (e.g., rolled fingerprints, palm prints, slaps) and later use those features to search for similar candidates in databases of millions of subjects. Formerly, it was known as FpVTE and was conducted previously in 2012.
