AI Agent for POS

Client Background

A leading European POS software product company.

Business Challenge

POS software company initiated a project to create an advanced cashier value added service. One of the key objectives was to enrich the platform with an AI-powered module that would help users — from physical stores business owners to cashiers and administrators — better understand their business performance and receive valuable insights.

However, the company lacked the in-house AI expertise required to design and implement this service. They needed an experienced partner to take full responsibility for the AI component — from research and concept design to full implementation and integration into the existing cashier ecosystem.

Solution

To bring the concept to life, our team developed an AI-agent module that seamlessly integrates with the cashier platform via iFrame and expands its capabilities with intelligent, data-driven features.

The module introduces an AI-powered chat that allows users to interact with their business data directly within the POS interface. The agent can analyze available information (e.g. list of goods, inventory data, suppliers, sales, organization settings, taxes, etc.) and assist users in evaluating business progress or identifying improvement areas.

In addition, the module features a recommendation system that provides AI-generated suggestions across a wide range of business areas — including, but not limited to, goods, marketing, receipts, analytics, and inventory. These recommendations are displayed as notifications inside the module and can also be shared with the main app via API to appear contextually on relevant pages.

The AI module applies role-based access controls to ensure data security and relevance — each user type, from cashier to owner, interacts only with the information available to their role. Through configurable rules, users can personalize how the AI operates within their own account, focusing on areas that are most relevant to them, such as inventory turnover or sales trends. This flexibility enhances the overall usefulness and adoption of the system.

POS system architecture

Results

The project was completed within 3 months, including integration with the main POS platform. Once released, the AI module is expected to significantly improve user engagement and operational efficiency by transforming raw business data into actionable insights and intelligent recommendations.