H1NTED - Sell Project

H1NTED is a pre-interaction AI personalisation technology designed to solve the cold-start problem for robots and AI agents. Instead of waiting for a system to build a profile through conversations, memory and feedback, H1NTED creates an initial behavioural context before communication begins. With user permission, the system analyses permitted non-biometric visual signals such as clothing and accessories. These signals are processed through H1NTED's proprietary methodology and probability-tree architecture to generate structured behavioural prompts. These prompts can instruct an AI agent or robot on factors such as communication style, wording, pacing, boundaries and approach for different interaction scenarios. The intended flow is: visual signals → H1NTED → behavioural instructions → AI/robot → personalised interaction. The technology has been developed as a working visual-assessment core and has been tested with different visual inputs and AI models. Earlier validation involved 110 users and reported 83% personalisation accuracy. Further permission-based testing during the feasibility work produced consistent results across different visual signals. The system is designed to complement, rather than replace, existing AI memory and history-based personalisation. H1NTED deliberately does not use facial recognition, identity recognition or biometric identification. Its current commercial direction is B2B, with the technology intended for integration into robotics and AI platforms.