> ## Documentation Index > Fetch the complete documentation index at: https://docs.generalrobotics.dev/llms.txt > Use this file to discover all available pages before exploring further. # Overview GRID provides a comprehensive suite of AI models for robotics — covering depth estimation, object detection, segmentation, vision-language understanding, robot control, and more. The fastest way to use these models is through **GRID Cortex**, our cloud-hosted inference service. Install the client, set your API key, and call any model in two lines of Python. Get started in 2 lines of code — unified API for all hosted models including depth, detection, segmentation, VLMs, robot control, and kinematics. ## Browse Models by Category For detailed per-model documentation (local inference wrappers using the `grid.model.*` package), browse by category: Models for perceiving depth from images, crucial for 3D scene understanding and obstacle avoidance. Identify and locate objects within an image or video stream. Models for finding corresponding points between images, essential for tasks like SLAM and image stitching. AI models to enable autonomous movement and path planning. Estimate the motion of objects or the camera itself between consecutive frames. Partition an image into multiple segments or regions, often to distinguish objects from the background. Enable a robot to build a map of an unknown environment while simultaneously keeping track of its location within that map. Follow the movement of specific objects over time in a video sequence. Estimate the time remaining before a potential collision, critical for safety systems. Models that can understand and respond to queries about visual content using natural language. Integrate visual information with natural language processing for enhanced understanding and interaction. Estimate the camera's motion by analyzing sequential camera images.