perceptron-mk1.5

Perceptron-mk1.5 is a multimodal reasoning engine specifically architected for embodied AI and physical agents. Unlike standard LLMs that treat vision as a secondary modality, this model is designed to bridge the gap between high-level semantic reasoning and spatial awareness. It processes interleaved text, image, video, and audio streams to drive decision-making in real-world environments. For developers, the standout feature is its ability to output not just natural language, but structured spatial annotations including bounding boxes, polygons, and temporal tracking data. This makes it a critical component for robotics, autonomous systems, and augmented reality applications where an agent must identify, locate, and track objects across time. It integrates via API, providing a scalable way to add complex spatial intelligence to existing hardware stacks without the overhead of training custom vision-language models from scratch.