California-based Robox AI has developed a configurable AI-powered platform that transforms compatible existing camera infrastructure into real-time actionable intelligence for loss prevention, safety, security, compliance and business operations.

Instead of requiring organisations to replace their existing camera infrastructure or deploy multiple single-purpose analytics products, Robox AI provides a centralised intelligence layer that supports multiple use cases across one location or an enterprise with many locations.

Built on a flexible edge-cloud architecture that connects with compatible existing IP camera environments, Robox AI combines AI technology with real-world security, loss-prevention and operational experience. Its on-site edge processing supports low-latency AI analysis, while its centralised software provides configuration, alert management, evidence, reporting and analytics across multiple locations.

The platform analyses configured video streams, identifies events based on defined criteria, delivers relevant alerts and supporting event evidence to authorised personnel based on user-defined rules, and connects those events to response, resolution, reporting and analytics.

It works with users to evaluate emerging problems, refine existing detection models and, where appropriate, develop or integrate additional capabilities, optimise workflows and measure results through an AI intelligence platform that advances alongside the organisations using it. This continuous-improvement model is intended to reduce the risk of organisations becoming locked into a static set of capabilities while their operating environment continues to change.

“We believe an AI platform should evolve, not be installed and then stand still while the problems around the customer continue to change,” said David Solomon, CEO of Robox AI. “Retail crime evolves. Safety risks evolve. Operational challenges evolve. Our responsibility should not end when the technology is deployed. Robox AI is built around an ongoing relationship with the customer. We work to understand the problem, configure the intelligence around that environment, refine the models, measure the results and evaluate new detection capabilities as needs change. The goal is not simply to give an organisation the AI it needs today, it is to provide an intelligence platform that can continue advancing with its business.”

Robox AI integrates video intelligence with transaction and other business-system data. For retail and grocery environments, PoS integration can add context for use cases such as sweethearting, scan anomalies, voids, refunds and other transaction-related events. Combining visual intelligence with relevant business data can provide additional context, improve event confidence and help organisations better understand what is occurring within the operation.

When a configured event is identified, authorised personnel receive relevant alerts and event evidence based on user-defined rules. The platform can then support the process beyond the initial detection through incident review, escalation, response documentation, resolution, reporting, historical analysis and management accountability. This allows organisations to move beyond using video simply to determine what happened after an incident. Instead, video can become a proactive source of operational intelligence.

Robox AI can be configured to support a range of use cases depending on the user’s environment, camera coverage, available data, operational priorities and deployment requirements, including:

• Retail and grocery: Shoplifting and concealment, cart push-outs, employee theft and sweethearting, self-checkout and transaction anomalies, loitering, crowd activity, fights and confrontations, queue conditions, out-of-stock conditions, unauthorised access, propped doors, slip-and-fall events, visible weapons, smoke or fire indicators, licence plate recognition, and additional customer-specific operational events.
• Restaurants and fast-food outlets: Queue and occupancy conditions, loitering, fights and confrontations, visible weapons, unauthorised access, propped doors, slip-and-fall events, PPE compliance, smoke or fire indicators, and selected operational-process deviations.
• Warehouses, distribution centres and manufacturing: PPE compliance, restricted-area activity, worker-down or fall events, forklift and vehicle-related safety conditions, propped doors, crowd conditions, asset or material removal, smoke or fire indicators, and selected operational-process deviations.
• Schools and other public environments: Visible weapons, fights and aggressive behaviour, loitering, crowd activity, unauthorised access, perimeter events, smoke or fire indicators, and licence plate recognition, subject to applicable policies, laws and deployment requirements.

Additional detections and integrations are evaluated based on user requirements, camera placement, operating environment, data availability and agreed deployment scope. Users can select and prioritise capabilities based on individual locations, risks, policies and operating objectives.

Los Angeles-based Robox AI (www.roboxai.com) develops configurable AI video intelligence that turns compatible existing camera infrastructure into actionable intelligence for loss prevention, safety, security, compliance and business operations. Its approach combines edge-based AI processing, configurable detection capabilities, business-system integrations, ongoing model refinement and operational expertise.