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AI-Powered Document Intelligence & Knowledge Platform

An intelligent ai document management platform combining multi-model AI, semantic search, and Retrieval Augmented Generation to simplify document analysis and knowledge discovery.

Overview

Docubox is an AI-powered document management and knowledge platform that transforms uploaded files into searchable, summarized information. Built with Next.js, TypeScript, Firebase, OpenAI, Google Gemini, and Anthropic Claude, the platform combines document processing, semantic search, and Retrieval Augmented Generation (RAG) to support natural-language questions and long-document analysis. Its multi-model AI architecture includes task-based routing, provider fallback, streaming responses, token tracking, and secure document access controls.
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Problem Statement

Time-Consuming Document Analysis

Reviewing lengthy documents manually makes it difficult to locate important information, summarize content, and extract relevant insights efficiently.

Limited Context and Information Retrieval

Sending entire documents to AI models can increase token consumption and make it harder to retrieve focused, relevant information from large files.

Dependence on Individual AI Providers

Different AI models have varying context limits, costs, and capabilities, creating a need for flexible model selection and reliable fallback handling.

Secure Document Access and Processing

Uploaded files, extracted content, and document metadata required structured processing, reliable storage, and access controls to protect user information.

Solution Statement

AI-Powered Document Intelligence

Developed document parsing, text extraction, chunking, and summarization workflows to turn PDFs, Word files, and image-based documents into usable knowledge.

RAG Pipeline and Semantic Search

Built an end-to-end retrieval pipeline using embeddings, relevant-passage selection, and contextual retrieval to support document Q&A and meaning-based search.

Flexible Multi-Model AI Orchestration

Integrated OpenAI, Gemini, and Claude through a unified layer with task-based routing, provider fallbacks, streaming output, and token-cost monitoring.

Secure Firebase Infrastructure

Implemented Firebase Authentication, Firestore, Cloud Storage, and security rules to manage document data and restrict access according to user permissions.

Features

  • Multi-Format Document Processing: Extract content from PDF, Word, and image-based files.
  • AI Document Summarization: Generate concise summaries of lengthy documents.
  • Natural-Language Q&A: Ask questions and retrieve relevant information from uploaded content.
  • RAG and Semantic Search: Find relevant passages through embeddings and contextual retrieval.
  • Multi-Model AI Integration: Route tasks across OpenAI, Gemini, and Claude.

Benifits

  • Faster Information Discovery: Locate relevant document content without manually reviewing every page.
  • More Focused AI Responses: Retrieve relevant passages to provide models with contextual information.
  • Flexible AI Capabilities: Select models according to task requirements, context needs, and cost considerations.
  • Improved Processing Efficiency: Chunking and retrieval help avoid sending entire long documents for every query.
  • Greater Operational Visibility: Token tracking, cost monitoring, and error monitoring support AI workload management.

About Techticks

Techticks delivers digital innovative solutions, including web and mobile apps, Ai integrations, and scalable systems. We help businesses grow, improve performance, and solve real-world challenges with secure, future-ready technology.

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