Real-time video processing at the edge. Frame-level analysis, AI inference, custom effects. <15ms latency, GPU acceleration, unlimited scale.
Process video frames in real-time with AI and custom effects
Direct access to video frames in real-time. Process, analyze, or transform each frame with <15ms latency. Perfect for effects, overlays, and content analysis.
Run TensorFlow Lite models for object detection, pose estimation, sentiment analysis. CPU or GPU acceleration. 5-12ms inference latency with unlimited model scale.
Deploy custom video effects as WASM modules. Render overlays, apply filters, composite graphics, or generate synthetic content. Sandboxed execution for security.
Functions receive stream metadata: resolution, framerate, bitrate, viewer count, geographic region. Make decisions based on stream characteristics and audience.
Optional GPU instances (T4, A100) for AI inference and complex effects. Auto-scaling handles GPU demand. Pay only for GPU time when invoked.
Processing runs on 200+ edge locations globally. Closest node to stream source processes frames. <15ms latency maintained across all regions.
Stream arrives at nearest EDGE node. Node receives stream metadata: resolution, framerate, bitrate, viewer count.
Video frames are extracted at processing framerate (10-30fps). Each frame is passed to processing pipeline.
WASM modules process frames: analysis, AI inference, effects rendering. <15ms per frame. Results stored in context.
Processed frames are re-encoded and streamed to viewers. Metadata and frame captures sent to VAULT and PULSE.
Real-time frame analysis for inappropriate content. Detect violence, nudity, or toxic elements. Flag for review or auto-blur. Works with RUNTIME webhooks.
Dynamically render logos, watermarks, or graphics based on stream context. Position overlays based on scene detection. Update branding in real-time.
Automatically detect exciting moments (goals, big plays) using frame analysis. Capture keyframes, extract clips, and publish highlights to VAULT. Feed into RUNTIME for distribution.
Analyze frame complexity and adjust encoding based on scene. Complex scenes (high motion) → higher bitrate. Static scenes → lower bitrate. 20-30% bandwidth savings.
Pay only for processing time. No infrastructure costs.
per ms
per ms
per GB-month
Example: Processing 100 concurrent 1080p streams at 30fps with object detection = ~$10-20/day. First 100K CPU-ms free monthly.
Start processing video frames in <15ms. Deploy custom effects, AI models, or content analysis pipelines.