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MES Solutions
LANCERProject Description
MES Solutions sought a real-time support system to streamline internal communication and automate customer query handling. With a growing user base, they needed a reliable chat integration that could scale with their support needs. The project required a smart chatbot interface connected to Rocket.Chat for seamless interaction between users and agents, powered by a robust backend architecture.
Scope Of Work
The client partnered with Oodles to replace fragmented customer conversations with a centralized, automated chat interface. Key objectives included building a conversational frontend, integrating it with Rocket.Chat, and enabling real-time communication with historical data access. The scope covered frontend UI setup, backend integration, live chat routing, database logging, and server deployment.
Our Solution
To meet these requirements, the project team designed and deployed a dual-server architecture using Django for the backend and Rocket.Chat for agent communication.
Key features and services implemented:
- Chatbot Interface Setup: Developed a dynamic frontend to capture user queries and display guided question flows.
- Real-Time Routing: Enabled routing of user chats to specific agents via Rocket.Chat based on the department or query type.
- Backend Development with Django: Built REST APIs to manage conversation logic, handle user input, and relay responses.
- Data Persistence: Stored all user conversations in a MySQL database for traceability and audit readiness.
- Conversation History: Integrated features to retrieve past chat logs for both users and agents to ensure continuity.