The company's approach centers on three core layers: perception, data acquisition, and world modeling. The DM-Tac series sensors serve as the foundation, utilizing vision-based technology to capture multidimensional data across 110,000 sensing units. This hardware feeds into the Data-Nexus system, which streamlines the production of interaction data for training. The final piece, the Daimon-TWM world model, integrates this information to enable robots to make predictive decisions based on force and material resistance.

In its first public demonstration since an August launch, the Daimon-TWM model is performing delicate, autonomous manipulation tasks that require more than just optical recognition. In one demonstration, a robotic arm strings tiny beads, a process necessitating the handling of deformable materials and constant adjustment to contact conditions. A second demo involves heat-transfer printing on tote bags, where the machine must execute a long-horizon sequence of peeling and stamping. By utilizing tactile feedback, the system moves beyond pre-programmed motion sequences, allowing the robot to anticipate the physical consequences of every movement in real time.