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3X Faster Answers in 10+ Languages with Smart LLM Chatbot Development

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.

application development services

90%

Reduction in Manual Overload

10+

Languages Supported

3X

Improvement in Query Resolution Time

Project Overview

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.

  • Industry - Media & Communication
  • Project Duration - 7 Months
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Project Scope & Challenges

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Multilingual & Context-Aware Architecture

An example of LangChain RAG implementation, the multilingual chatbot is tailored to support multilingual interactions and ensure accurate responses across different user contexts.

Session Continuity & Follow-Up Handling

A key challenge was enabling smooth session memory and context retention so users could ask follow-up questions without losing conversational continuity.

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Intelligent Query Handling

Integrated vector search using pgvector and session memory to enhance document retrieval accuracy and ensure semantic understanding of user queries.

Seamless Platform Integration

Connected the conversational AI chatbot across Slack, Teams, Outlook, and WhatsApp using respective APIs, ensuring uniform behavior and responsiveness on each platform.

Seasia’s Solutions

By transforming Orchestro AI’s communication stack into a powerful, Artificial Intelligence solutions , 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.

Key Highlights

01

RAG Architecture 

Developed using Langchain to deliver intelligent, prompt-based responses integrated with Orchestro_AI's knowledge base 

02

Session Memory

Ensured continuity in conversations by storing context-aware session data 

03

Multilingual Support 

Enabled real-time conversations in over 10+ languages, ensuring global usability 

04

Cross-Platform Integration 

Integrated with Slack API, Microsoft Graph API (Outlook, Teams), and WhatsApp Business API 

05

Vector Search Implementation

Used pgvector with PostgreSQL for high-accuracy document retrieval 

06

FastAPI & Python Backend 

Built a high-performance API layer to manage interaction workflows

Our Technology Stack

Framework

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Programming Language

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Data Handling

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Embeddings

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API Development

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Cloud & Deployment

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Results & Achievements

  • 70% reduction in manual workload by automating query handling
  • 3x improvement in query resolution time
  • Higher accuracy in query intent classification using vector-enhanced search
  • Multilingual support across 10+ languages, boosting global accessibility
  • Improved document retrieval accuracy and relevance, enhancing user trust and experience

Intelligent, Context-Aware Chatbots for the Media & Communication Industry

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.

Contact for Custom AI Chatbot
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Success Stories

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Seasia is a trusted IT software development company has been delivering top-notch software consulting and solutions to businesses across the world for over two decades now.

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