Achieved 80% user satisfaction in customer support automation
Reduced manual ticket handling for routine inquiries
Enabled support team to focus on high-value interactions
Serverless architecture minimized operational overhead
Challenge
A SaaS company's support team was overwhelmed with repetitive inquiries. Manual ticket handling was slow, inconsistent, and prevented the team from focusing on complex customer issues.
Solution
I integrated a serverless RAG-based AI agent architecture using OpenAI, LangChain, Qdrant, Airflow, and AWS Lambda. The system automated routine inquiries while maintaining quality through vector-based retrieval and contextual responses.
My Role
AI/ML Engineer – designed the RAG architecture, built the vector pipeline, and integrated with existing support infrastructure.
Key Deliverables
- 01RAG-based AI agent using LangChain and OpenAI
- 02Qdrant vector database for semantic search
- 03Airflow-orchestrated document ingestion pipeline
- 04AWS Lambda serverless deployment for cost efficiency
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