Reliable Integer Ambiguity Resolution (IAR) of carrier-phase measurements is critical for Global Navigation Satellite Systems (GNSS) high accuracy positioning.  State-of-the-art IAR strategies employ well-established processes (float estimation, decorrelation and searching) which, however, cannot deem efficient for real-time kinematic applications. Analytically, by virtue of weak models, biases and the ever-increasing number of tracked satellites, IAR is characterized as an NP-Hard problem suggesting that ambiguities cannot always be fixed reliably and efficiently leading to solutions of deteriorated quality, particularly in GNSS-harsh environments. To address this issue, CLARITY adopts Artificial Intelligence (AI) approach and tools aiming at investigating, effectively implementing and evaluating cutting-edge AI concepts for reliable ambiguity resolution addressing also multi-frequency and multi-system scenarios.