🤖 AI Chatbot for FinTech — Intelligent Transaction Query Assistant
This repository accompanies tutorial on building an AI-powered chatbot that integrates RAG (Retrieval-Augmented Generation) and LangChain to interact with financial data securely and intelligently.
The chatbot connects with your organization’s transactional database to answer natural language queries such as:
💳 “What’s the status of my last transaction?”
📊 “How many transactions were processed today?”
💰 “Show me all transactions above $1,000 last week.”
📈 “What’s the total transaction volume for this month?”
🚀 Key Features
AI-Powered Query Engine: Uses LangChain and RAG pipelines to interpret natural language and fetch accurate responses from structured financial databases.
FinTech Use Cases: Ideal for banks, payment gateways, and financial platforms to provide intelligent self-service analytics and transaction insights.
Secure and Compliant: Designed with data privacy, audit trails, and access control in mind.
Full-Stack Integration: Vue.js + Node.js + TypeScript front-end and back-end, with REST/GraphQL APIs and ElasticSearch for optimized query performance.
Cloud-Ready Deployment: CI/CD pipelines, containerization, and monitoring support for Azure, AWS, and OpenShift (OCP4).
🧠 Tech Stack
Frontend: Vue.js, TypeScript
Backend: Node.js, Express, REST/GraphQL APIs
AI/ML: LangChain, RAG, Model Training, LLM Integration
Database: SQL / NoSQL with ElasticSearch for intelligent search and indexing
Cloud & DevOps: Azure, AWS, OCP4, Docker, CI/CD
Monitoring: Dynatrace, Kibana, Prometheus
📩 Connect
If you’re exploring AI in FinTech, building intelligent assistants for banking or analytics, or just curious about applied LangChain + RAG, feel free to connect!
💬 Telegram: @PatelNisarg28