RAG AI Agent & Chatbot
Jakub Dzikowski
RAG Agent on complex financial data ⚡
Overview 🚀
Recently developed RAG (Retrieval-Augmented Generation) agent for a wealth management firm looking to simplify financial data retrieval. Swiftly launched, this project showcases just how quickly AI solutions can go from concept to reality when you combine the right tools and expertise.
Key Challenges ⚖️
Complex Data: Clients needed to quickly access details on portfolios, market performance, and compliance data without combing through endless documents.
Speedy Delivery: The project had to be built and deployed in just a few days, testing my ability to prototype at lightning speed.
User-Friendly Design: Financial advisors and their clients needed a simple, intuitive way to query information—even if they weren’t tech-savvy.
Simple RAG Interface
Approach ✨
Rapid Prototyping
Broke down the chatbot’s scope into core features (data retrieval, natural language queries, user interface).
Prioritized essential functionalities to ensure a functioning MVP within the tight deadline.
Tailored Financial Use Cases
Modeled the chatbot’s flow around typical user questions: portfolio overviews, compliance checks, and market insights.
Ensured responses included clear references and data points, building trust with end users.
Tech Stack Highlights 🛠️
LlamaIndex: Powered the chatbot with robust retrieval capabilities, ensuring accurate information from large financial datasets.
Next.js: Provided a fast, modern front-end framework, making the final product responsive and easy to navigate.
AI-Driven Backend: Combined advanced NLP and knowledge base indexing for quick, context-aware answers.
RAG Answering Complex Questions
Results & Impact ⭐
Instant Data Retrieval: Users can ask questions in plain language and get accurate, concise answers in seconds, cutting research time drastically.
Enhanced Client Satisfaction: A sleek interface and immediate insights empower wealth managers to offer proactive advice, boosting their credibility.
Proven Agility: Demonstrated how an MVP can be built and launched in under a week, showing that AI innovation doesn’t need to be slow or complicated.
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Posted Jan 6, 2025
A LlamaIndex RAG chatbot MVP built for a wealth management company to simplify data retrieval. Delivered in a week with a clean Next.js interface. ⚡
