Investment Proposal for AI-Based Academic Information Retrieval, Summarization, and Analysis Solution Development
1. Company Introduction
- Company Name: Deep Network
- Established: 2023
- CEO: Seokweon Jang / sayhi7@daum.net
- Business Area: Development of AI-Based Academic Information Retrieval, Summarization, and Analysis Solutions
Deep Network is a one-person startup specializing in the construction of academic paper and algorithm summarization services based on AI-powered search and summarization technology. Since its establishment, the company has analyzed and advanced numerous cutting-edge AI models and machine learning (ML) algorithms over approximately two years, laying a technical foundation for service implementation. Additionally, Deep Network has successfully designed and prototyped an AI search engine capable of parsing academic papers and automatically summarizing algorithms and formulas, and now proposes the business potential of this service.
2. Business Background and Problem Definition
Currently, numerous researchers and corporate personnel face difficulties in searching and reviewing a vast number of papers in academic databases such as arXiv. The sheer volume of information, along with the complexity of the formulas and algorithms within the papers, makes efficient learning and rapid insight extraction challenging.
Thus, Deep Network focuses on developing an AI-based service that analyzes and summarizes key algorithms and formulas within papers, proposing a solution that enhances user productivity and supports new research and development ideas.
3. Service Overview and Key Features
Deep Network's AI-based academic paper summarization service consists of the following key features:
- Automatic Parsing and Text Extraction: Extracts text and formulas from PDF files crawled from academic sites like arXiv.
- Formula Recognition and Conversion: Converts formulas within papers into LaTeX or MathML, parses them, and processes them in a formula analysis engine to derive key operations and concepts.
- Core Content Summarization: Uses deep learning-based natural language processing (NLP) models to generate summaries of the paper's key concepts, results, and formulas.
- AI-Based Search and Filtering: Allows users to quickly find relevant papers through customized searches and filtering based on titles, keywords, and topics.
- User-Customized Interface: Visualizes paper analysis results according to research purposes, allowing users to selectively view topics or algorithms of interest.
4. Service Architecture
Deep Network's AI service is composed of the following key modules:
- Crawling and Data Collection System: Analyzes crawlers and automated systems that collect paper links and metadata from sites like arXiv. Provides user-customized paper updates, including rate limiting and automated scheduling to prevent excessive requests.
- PDF Parsing and Text Extraction System: Identifies and converts text and formulas within papers using libraries such as PDFBox and PyMuPDF. Utilizes a self-developed parsing algorithm for accurate extraction of text and formulas.
- Formula Recognition and Analysis Engine: Recognizes and interprets complex formulas from papers through a formula parsing engine, summarizing key algorithms. Converts formulas in MathML and LaTeX formats into text for user comprehension and summarization.
- Deep Learning-Based Summarization and NLP Model: Implements functions that summarize important sentences and key contents of papers using the latest transformer-based large language models (LLM). Develops academic paper-specific summarization models by fine-tuning models like BERT and GPT.
- Data Management and Search System: Optimizes indexing and filtering performance of papers using Elasticsearch, supporting searches by paper title, author, and keywords. Manages paper data efficiently using NoSQL DBs like MongoDB.
5. Technical Know-How
Deep Network secures core technologies for service implementation through the following technical differentiators:
- Customized PDF parsing technology for various paper formats
- Formula parsing and complex algorithm analysis technology
- Implementation and optimization of trained transformer models for automatic paper summarization
- Construction of a high-performance search engine based on Elasticsearch
6. Target Market and Business Expansion Potential
- Research and Academic Institutions: Main customers include researchers, universities, and research institutes, supporting improved research outcomes through efficient academic information provision.
- Corporate R&D Departments: High expected utilization of paper analysis services in AI research and technology development departments.
- Education Sector: Useful for university and graduate-level lectures and research processes through the paper summarization service.
7. Commercialization Strategy
- Subscription Model: Users pay a subscription fee for regularly provided paper formula and algorithm summaries.
- API Provision: Provides paper search and summarization APIs to corporate research labs and educational institutions for use as a research platform.
- Partnership Strategy: Expands and improves accessibility of the paper summarization service through partnerships with academic databases.
8. Revenue Model and Expected Revenue
- Subscription Service for Research Institutions and Corporations: Expects stable revenue generation through monthly subscription services with advanced summarization and formula analysis features.
- API Usage Fees: Generates additional revenue by providing customized search and summarization features to corporations based on API usage volume.
9. Purpose of Investment and Expected Use of Funds
Deep Network aims to secure [amount] won in investment for initial service launch and technical expansion. The main funding usage plan includes:
- Expansion of Development Personnel: Hiring specialists for deep learning model improvement and system development
- Infrastructure Expansion: Building high-performance GPU servers and cloud infrastructure
- Marketing and Sales: Strengthening marketing and promotional activities targeting research institutions and corporations
10. Conclusion
Deep Network's AI-based academic paper summarization service holds the potential to play a significant role in the rapidly developing AI research and information utilization market. Beyond simple paper search, this service provides a core understanding of algorithms and formulas, significantly enhancing researchers' efficiency and supporting new research and development ideas. Thus, Deep Network seeks to improve technical completion through initial investment attraction and lay the groundwork for commercialization.
[Investment Inquiries] Contact: sayhi7@daum.net / Contact Person: CEO / Seokweon Jang