Overview
SmartChat is an enterprise-grade SaaS solution designed to bridge the gap between static business data and active customer support. By transforming internal documents and FAQs into an intelligent conversational layer, the platform allows companies to automate up to 80% of routine inquiries with high factual accuracy.
My Role: Full-Stack AI Engineer
As the lead Full-Stack AI Engineer, I architected the end-to-end RAG (Retrieval-Augmented Generation) pipeline and managed the integration of AWS cloud services. My primary focus was on ensuring “data grounding” — preventing AI hallucinations by strictly anchoring responses to users’ uploaded business documents via a high-performance vector database.
Key Features
- 🧠 Hybrid RAG Pipeline — Utilizes LangChain to orchestrate OpenAI and open-source LLMs, ensuring context-aware and brand-aligned responses.
- 📂 Secure Document Intelligence — Integrated AWS Textract and Rekognition for advanced OCR and image analysis, allowing the bot to read complex PDFs and diagrams.
- 📈 Real-Time Analytics — A robust dashboard that tracks user intent, chat volume, and resolution rates, providing actionable support insights.
- 🚀 Omnichannel Deployment — Supports 1-click web embeds, standalone public links, and developer-friendly REST APIs.
- 🛡️ Enterprise Security — Implements secure file handling with AWS S3 and encrypted metadata storage to protect client data.
Tech Stack
- Frontend: Next.js, Tailwind CSS, TypeScript
- Backend: Node.js, LangChain
- AI & Data: OpenAI API, Pinecone (Vector DB), Open-Source LLMs (Llama/Mistral)
- Cloud Infrastructure: AWS (S3, Textract, Rekognition, Lambda)
- Deliverables: Full-Stack Development, AI Chatbot Architecture, SaaS Multi-tenancy, AWS Integration
Why I Built This
Modern businesses are overwhelmed by repetitive support tickets, yet traditional chatbots often frustrate users with rigid, scripted answers. I built SmartChat to provide a plug-and-play AI employee that understands each company’s unique documentation, making enterprise-grade AI accessible without requiring a dedicated DevOps team.
Links
- 🔗 Live Demo
- 💾 Source Code
Automating intelligence for the modern enterprise.