Back to Solutions

KiengCore

RAG Backend Platform

Description & Purpose

KiengCore is a comprehensive RAG (Retrieval-Augmented Generation) backend platform that revolutionizes how organizations interact with their document repositories. By combining advanced document processing capabilities with intelligent AI chat and voice interactions, KiengCore enables users to upload documents and engage in natural, contextual conversations with their data. The platform leverages cutting-edge retrieval-augmented generation technology to provide accurate, relevant responses based on the uploaded content, making information discovery and knowledge extraction more intuitive and efficient than ever before.

Smart Document Processing

Upload and process various document formats including PDFs, Word documents, text files, and more. Our advanced parsing technology extracts and indexes content for optimal retrieval performance.

AI-Powered Chat Interface

Engage in natural conversations with your documents through our intelligent chat interface. Ask questions, request summaries, and explore content through intuitive dialogue.

Voice Interaction Capabilities

Experience hands-free document interaction through advanced voice recognition and synthesis. Speak your queries and receive audio responses for a truly conversational experience.

Problem Solved

Key Features

Technology Stack

Backend: Python RAG Framework: LangChain Vector Database: Pinecone/Chroma LLM Integration: OpenAI/Anthropic Document Processing: PyPDF2/python-docx Voice Processing: Whisper/ElevenLabs Frontend: React/NextJS API: FastAPI Deployment: Docker/Kubernetes

Use Cases