Recognise
AI-based product detection identifies supported fruits and vegetables from the store's configured item list.
Recognize. Weigh. Bill. Jini's AI POS combines AI vision, integrated weighing, automated billing and payment into one intelligent retail system designed for grocery, fresh-produce and bakery environments.

The original RNI AI POS specification describes a custom-built AI software system for detection of fruits and vegetables, supported by dedicated hardware, an integrated weighing system and automated transaction workflows.
AI-based product detection identifies supported fruits and vegetables from the store's configured item list.
An integrated weighing platform captures the quantity/weight required for the transaction.
Product, price and quantity/weight information can be combined into a structured transaction.
Automated billing and payment complete the customer transaction and create digital operational data.
A simple graphical view of how the AI POS brings physical retail activity into one digital workflow.
Based on the original Jini's AI POS specification provided to RNI, the system combines dedicated computing, AI vision, touch-based operation, weighing and automated physical components.
Talk to RNIAI vision is designed to recognise supported fruits and vegetables from the configured store list.
The supplied specification states capability for up to 110 items, subject to the store list and implementation configuration.
The concept includes the capability to learn new items introduced by the user.
The supplied specification identifies weighing capacity up to 30 kg for the proposed integrated platform.
Transaction data can flow from recognition and weighing into automated billing and payment workflows.
Once transactions are digital, sales and inventory information can support dashboards and further automation.
These visuals represent the Jini's AI POS concept and the RNI-branded product experience developed during the product design work.



Camera, display, weighing platform, printer and selected automated hardware components.
Recognition, transaction logic, billing, payment and structured product information.
Sales visibility, inventory information, dashboards and future AI/analytics extensions.
The final configuration should be defined around the customer's actual operating environment, product catalogue and transaction model.
Recognition and weighing can simplify transactions for fruits and vegetables.
High-volume counters can benefit from faster, more structured billing workflows.
Connect POS activity with product, sales and inventory information.
Use AI recognition and automation as the foundation for self-service concepts.
Jini's AI POS is RNI's AI-based automated POS concept combining product recognition, weighing, billing, payment and retail data capture.
The original specification focuses on fruits and vegetables and states a capability of up to 110 items based on the store list provided. The final recognition catalogue depends on configuration and training.
Yes. The supplied system specification includes a customised integrated weighing scale and identifies a weighing capacity of up to 30 kg.
The supplied specification includes the capability of learning new items introduced by the user, subject to the final AI implementation.
Yes. Hardware, product catalogue, transaction workflow, payment integration, dashboards and other integrations should be finalised based on the deployment environment.
Tell RNI about your retail, fresh-produce, canteen or smart-kiosk environment. We can map the product-recognition, weighing, billing and intelligence requirements into a practical deployment architecture.