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RBOX - AI FOR RETAIL
Runs on any hardware you already own
Intel, AMD, or ARM, on store servers, back-office workstations, warehouse systems, or cloud tenancy. No new infrastructure required.
Customer and transaction data stays yours
Every input, output, and log stays within your environment. Full ownership of customer data, purchase history, and business intelligence, no third-party access.
Works in the store, not just the cloud
AI runs at the point of operation, on the shop floor, in the stockroom, at the checkout, without internet dependency or cloud round-trips slowing real-time decisions.
AI in the language of your market
Multilingual model support for customer-facing tools across regions, languages, and demographics.
Cloud-based AI works well on paper. In practice, retail means stores with patchy connectivity, warehouses with legacy hardware, and margins that don't survive per-query cloud billing. Most retailers either overbuild for AI they can't afford to run, or underbuild and miss the opportunity entirely.
RBox fits into what you already have. On store servers, on existing back-office hardware, on your cloud tenancy, or all three at once. One runtime, every environment, no new infrastructure required.
New to RBox? These videos cover the full picture, what RBox is built for, what it can do,
and how to deploy it across your retail network.
RBox runs text, speech, vision, and multimodal models, at the store, at the warehouse, in the
cloud, all configurable to your retail workflows.
Run AI models on sales history, seasonal trends, and supply chain data, without sending business-critical data to external services.
e.g. A retail chain runs daily demand forecasts across 200 stores on existing back-office hardware. No data shared externally.
Use vision models to monitor shelf occupancy, planogram compliance, and product placement, processed on store hardware in real time.
e.g. A supermarket chain analyses shelf images from in-store cameras on local servers, triggering restocking alerts without any image data leaving the store.
Deploy multilingual AI assistants for product queries, recommendations, and support, responding in your customer's language.
e.g. A large format electronics retailer deploys an AI product advisor available in 5 regional languages.
Analyse purchase patterns, competitor pricing, and customer behaviour data to generate dynamic pricing and promotion recommendations without external data exposure.
e.g. A departmental store chain runs real-time promotion models on purchase data across all outlets.
Run AI on logistics, delivery, and supplier data to optimise routing, predict delays, and manage vendor performance.
e.g. A distribution network runs daily route optimisation on warehouse hardware - no data sent to external logistics AI platforms.
Deploy vision and behavioural models for shrinkage detection, anomaly flagging, and loss prevention
e.g. A retail chain processes CCTV feeds locally using RBox vision models, flagging anomalies in real time without video data leaving the premises.
From first install to production deployment, every step is walked through on video. Whether you're integrating via REST or an SDK, configuring multi-tenancy across store locations, or scaling inference across NUMA nodes, you'll find a dedicated walkthrough covering it end to end.
RBox is filtered and configured for retail. Every capability carries the same privacy and performance guarantees.
Works on Intel AMX, AVX-512, ARM SVX, and AMD processors — the CPUs in your store servers, warehouse systems, and back-office hardware. No specialised infrastructure. NUMA-aware for multi-socket systems.
RBox runs inference locally, making it suitable for stores and warehouses with limited or unreliable connectivity.
All processing happens within your infrastructure. Customer purchase history, behavioural data, and transaction records never reach Kompact AI or any third party.
Serve multiple store locations, regional teams, and business units from a single deployment with built-in JWT-based access isolation. Each location gets its own access and usage visibility.
Low-latency AI responses for shelf analytics, customer interactions, and loss prevention.
Integrate RBox into your existing POS, ERP, CRM, and inventory systems using OpenAI-compatible REST APIs and SDKs in Java, C#, Python, JavaScript, Kotlin, C++, and Rust.
CPU-based inference runs on already-allocated store and warehouse power. No new load on your infrastructure, no additional energy costs.
RBox deployments are fully self-contained at each location. No centralised infrastructure required. Scale to hundreds of stores without adding central dependency or single points of failure.
Kompact AI delivers 2x higher performance than any other AI inference software , on the same hardware you already own.
Across long customer interaction histories, multi-session conversations, and extended analytical workflows.
All processing happens inside your infrastructure. Customer purchase data, behavioural patterns, and transaction records are never sent to Kompact AI or any third party.
Customers retail data is never used to retrain or improve any model. Customer intelligence and business data stays within your environment.
AuthN and AuthZ built in. Control exactly which teams, store managers, and systems can access which models and outputs, at every level of your organisation.
Every AI output is traceable to the exact model version that produced it. Full audit trail for internal governance, promotional accountability, and regulatory review.
By keeping all AI workloads within your controlled infrastructure, RBox helps you operate in alignment with consumer data protection frameworks — DPDP, GDPR, and regional equivalents without Kompact AI ever seeing or storing customer data.
Your customer intelligence is yours. Your business logic stays in your environment.
No. RBox runs on Intel, AMD, and ARM processors already in most retail back-office and warehouse systems. It is compatible with Ubuntu, Red Hat, CentOS, Fedora, and Suse. No new hardware or power infrastructure required.
RBox runs entirely within your infrastructure. All inputs, model outputs, and logs stay inside your environment regardless of the underlying hardware or OS. Customer data is never sent to Kompact AI or any external service.
Yes. RBox deployments are self-contained at each location; no centralised infrastructure required. Each store runs its own instance independently. The Kompact AI Gateway handles scaling for concurrent users within a single location.
RBox exposes an OpenAI-compatible REST API, enabling integration with most modern POS, ERP, CRM, and inventory platforms without bespoke engineering. SDKs are available in Java, C#, JavaScript, Python, and more.
RBox runs on existing hardware with no additional power draw and no per-query cloud billing. Licensing scales with your deployment - not your usage or transaction volume. The larger your network, the more you save versus cloud-based alternatives.
See RBox running on your infrastructure. Get in touch.
RUN AI ON MY INFRASTRUCTURE
