AI Commerce Agent
An AI system to automate customer service and sales across social messaging platforms, all powered by AI.
Technologies used:
12 Dec 2025
Kuwait
The Vision & Challenge
A direct-to-consumer fashion retailer in Kuwait built its business on personal connections, using WhatsApp and Instagram for sales and support. This high-touch model was central to their brand but created a natural limit to their growth.
The reliance on manual, one-to-one conversations meant operational costs scaled directly with customer volume. Support was confined to business hours, response quality was inconsistent across agents, and valuable customer data was lost in unstructured chat logs. The business could not grow without solving this operational bottleneck.
Robust Devs was brought in to design an automation layer that could handle the complexity of social commerce. We developed a central AI orchestrator that integrates directly with their existing tools, automating nearly 90% of customer interactions from product questions to final payment.
Project challenges
- The client's core systems-WooCommerce, messaging apps, and payment gateways-operated in isolation, requiring agents to manually look up products and create orders.
- Customer inquiries were multimodal and multilingual. The system had to accurately process text, images, and voice notes in both Arabic and English to be effective.
- A purely automated system risked alienating customers with complex needs. The platform needed to discern when a human touch was required and escalate intelligently.
Solutions
- We built a central API to act as the system's core. This orchestrator connects in real-time to the WooCommerce database for live inventory, the MyFatoorah API for payment link generation, and Respond.io for human support.
- The orchestrator was integrated with multiple specialized AI models. We used language models for conversation, Whisper API for voice transcription, and Vision API to identify products from customer images.
- We designed a context-aware handoff mechanism. The system analyzes conversation sentiment and flags inquiries it cannot resolve, then transfers the user to a human agent with the full conversation history and a summary of their intent.
Technologies used
We are concerned about the security and performance of our customers. That's why we always keep updating and use best technologies in our products
Back-end
Python
NodeJS
DevOps
Docker
Github CI
Database
Mongo DB
Central AI Orchestrator
The orchestrator is the system's brain. It processes all incoming messages, manages the business logic, and routes requests to the correct internal or third-party service. This central-hub architecture ensures all interactions are consistent, logged, and easy to update, without being tied to any single front-end messaging platform.
Context-Aware Human Handoff
When a conversation requires human intervention, the system does more than just transfer the chat. It analyzes the dialogue to determine the customer's goal, then packages the entire conversation history and a data summary for the agent. This allows for a fluid transition where the customer never has to repeat themselves.