Enables deterministic reconstruction of complex tables from OCR bounding boxes, including multi-column layouts, merged headers, grid hierarchies, formula auditing, and PII redaction through MCP.
Enables AI agents to fuse 2D/3D visual bounding boxes, user head-pose gaze vectors, and acoustic beamforming azimuth angles into cross-modal focal salience scores. It also resolves deictic spatial references in real time, running as a zero-dependency Python MCP server over JSON-RPC stdio.
Enables autonomous shortform video editing by converting 16:9 footage to 9:16 with dynamic speaker tracking, smart reframing bounding boxes, audio silence pacing, and precise cut-list generation through MCP-compatible clients.
Enables autonomous agents to orchestrate HubX mobile AI tools for plant and nutrition vision diagnostics, voice transcription and summarization, photo-realistic portrait and art generation, and interior/exterior spatial design through structured JSON outputs.
Enables audio silence detection and jumpcut cadence/pacing analysis for shortform video editing, producing precise cut-lists and telemetry through the Model Context Protocol.
Enables agents to turn ambient visual wallpapers and lifestyle scenes into personalized retail product recommendations and one-tap shopping actions via MCP.
Enables edge robotics to slice LiDAR/depth point clouds into 2.5D occupancy grids, computing spatial obstacles for real-time telemetry and actuator safety supervision.
Enables high-resolution image canvas processing by slicing images into spatial grid tiles and blending seams for seamless generative upscaling, compatible with Magnific AI / Krea AI workflows.
Provides multimodal OCR table grid and merged-cell reconstruction into Markdown, and integrates with MCP-compliant clients like Claude Desktop and Cursor.
Enables MCP clients to score the retention quality of the first three seconds of shortform video hooks using audio/video telemetry and transcript input, returning deterministic JSON results for viral hook optimization.