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Seasia Infotech partnered with Orchestro AI to design an intelligent LLM-powered chatbot that streamlines internal and external communication across platforms like WhatsApp, Slack, Microsoft Teams, and Outlook. The client organization wanted to reduce manual workload, improve turnaround time for queries, and deliver actionable insights through intelligent, natural-language interactions.
Reduction in Manual Overload
Languages Supported
Improvement in Query Resolution Time
Orchestro AI is a technology-driven organization focused on streamlining business operations through intelligent automation and data-driven insights. The LLM-based chatbot solution was envisioned as an AI-first LLM Retrieve-Augment Generate (RAG) chatbot to interact with internal APIs and databases, deliver real-time answers, maintain context across sessions, and support multilingual conversations for a global user base.
An example of LangChain RAG implementation, the multilingual chatbot is tailored to support multilingual interactions and ensure accurate responses across different user contexts.
A key challenge was enabling smooth session memory and context retention so users could ask follow-up questions without losing conversational continuity.
Integrated vector search using pgvector and session memory to enhance document retrieval accuracy and ensure semantic understanding of user queries.
Connected the conversational AI chatbot across Slack, Teams, Outlook, and WhatsApp using respective APIs, ensuring uniform behavior and responsiveness on each platform.
By transforming Orchestro AI’s communication stack into a powerful, AI-driven interface, Seasia helped unlock faster decision-making, consistent support, and scalable automation across teams. The project stands as a testament to the power of LLM-backed conversational AI in redefining enterprise productivity and engagement.
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