We build video analysis systems that detect events, track objects, classify actions, and extract insights from video streams and recordings in real time.
Video is the richest data source available but also the most difficult to analyze at scale. Hours of footage accumulate daily from security cameras, production lines, retail floors, and content platforms. AI video analysis automates the extraction of actionable intelligence from this visual data, detecting events, tracking objects, and identifying patterns that would require armies of human monitors to catch.
Modern video AI combines frame-level image analysis with temporal understanding that recognizes actions, events, and patterns over time. A person walking through a frame is a detection. The same person entering a restricted area is an event. That person returning to the same area repeatedly at unusual hours is a pattern. Each level of analysis requires progressively more sophisticated AI.
Arthiq builds video analysis solutions for security and surveillance, manufacturing quality control, retail analytics, content moderation, and sports and entertainment applications. Our systems process both live streams for real-time alerting and recorded footage for retrospective analysis.
Processing video in real time requires specialized architecture that handles the high data throughput of video streams. Arthiq builds video processing pipelines that decode video frames, run AI inference, and deliver results with latency measured in milliseconds. Our architectures use GPU acceleration, frame sampling strategies, and multi-stream multiplexing to process dozens of simultaneous camera feeds on cost-effective hardware.
Not every frame needs full analysis. We implement intelligent frame sampling that processes every frame during periods of activity and reduces sampling during quiet periods. Motion detection triggers full analysis only when something worth analyzing is happening, dramatically reducing compute requirements without missing events.
Our edge computing deployments run video analysis directly on cameras or local servers, minimizing bandwidth requirements and enabling offline operation. Only events and metadata are transmitted to the cloud, rather than raw video streams. For privacy-sensitive applications, this architecture ensures that video data never leaves the premises.
Object detection identifies what is in each frame: people, vehicles, products, equipment, or any domain-specific object. Object tracking follows detected objects across frames, maintaining identity as they move through the scene. Combined, detection and tracking answer questions like "how many people entered the store, how long did they spend in each department, and which route did they take."
Action recognition identifies what is happening in the video: a person falling, a vehicle stopping, a machine malfunctioning, or a product being picked up. We train action recognition models on your specific scenarios to detect the events that matter for your application.
Event composition combines low-level detections and actions into meaningful business events. A "shoplifting event" might be composed of a person picking up an item, putting it in their bag without scanning, and approaching the exit. We define these event compositions based on your operational requirements and implement them as configurable rules on top of the AI detection layer.
For recorded video content, AI enables intelligent indexing and search. We build systems that analyze video content, identify scenes, detect objects and people, transcribe speech, and generate searchable metadata that makes large video libraries navigable. Users can search for specific visual content, find all instances of a particular event, or navigate to the exact moment something of interest occurred.
Content moderation for video platforms uses AI to detect inappropriate content, copyright violations, and policy violations at upload time or during live streams. Our moderation systems process video frames and audio simultaneously, catching issues that would be missed by analyzing either modality alone.
Video summarization condenses long recordings into highlight reels or textual summaries. Meeting recordings are summarized into key discussion points. Surveillance footage is condensed into a timeline of events. Production recordings highlight quality incidents. These summaries save hours of video review time.
Video analysis is one of the most technically demanding AI applications, requiring expertise in computer vision, real-time systems, and scalable infrastructure. Arthiq brings all of these capabilities together to deliver video AI solutions that work reliably in production.
We start video projects with a proof of concept using your actual video data, demonstrating detection and analysis accuracy before committing to full implementation. This approach validates feasibility early and ensures the final system meets your operational requirements.
Contact us at founders@arthiq.co to discuss how AI video analysis can add intelligence to your video data.
Our team will build video analysis systems that extract actionable intelligence from your video streams and recordings with real-time performance and production-grade reliability.