๐Ÿš€ Building a Customer 360 Multi-Agent Copilot with LangChain
Excited to join the upcoming AI Guild Workshop by Decoding Data Science
Organized by Mohammad Arshad, this session will provide a practical deep dive into how modern AI systems are built using:
โœ… Multi-Agent Orchestration
โœ… LangChain
โœ… SQL Agents
โœ… RAG (Retrieval-Augmented Generation)
โœ… Customer Data Agents
โœ… AI-Powered Customer Care Automation
๐Ÿ’ก Why this session is valuable?
Todayโ€™s businesses generate massive amounts of customer data, but transforming that data into actionable insights is the real challenge. This workshop demonstrates how AI agents can collaborate together to create intelligent customer support and recommendation systems.
๐Ÿ“Š Real-World Applications:
๐Ÿ”น Customer 360 platforms
๐Ÿ”น AI customer support systems
๐Ÿ”น Recommendation engines
๐Ÿ”น Business intelligence automation
๐Ÿ”น Personalized customer experiences
๐Ÿ”น AI copilots for enterprises
๐Ÿค– How it impacts AI & Data Analytics:
Combines structured SQL data with AI reasoning
Uses RAG pipelines to improve AI responses
Connects analytics, automation, and customer intelligence
Demonstrates the future of intelligent enterprise systems
This is an excellent opportunity for:
โœ” AI Engineers
โœ” Data Analysts
โœ” Data Scientists
โœ” Software Developers
โœ” ML Engineers
โœ” Business Intelligence Professionals
Looking forward to learning from this technical deep dive for AI builders! ๐Ÿ”ฅ
#AI #LangChain #DataScience #MachineLearning #ArtificialIntelligence #RAG #SQL #LLM #GenerativeAI #Customer360 #DataAnalytics #Automation #DDS #TechLearning
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Nipun Kavinda
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๐Ÿš€ Building a Customer 360 Multi-Agent Copilot with LangChain
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