OpenDraft is an open source AI research draft generator that uses 19 specialized AI agents to create academic paper drafts with verified citations. It searches real academic databases (Semantic Scholar, CrossRef, arXiv) and produces properly formatted papers.

How does the multi-agent system work?

OpenDraft uses 19 specialized AI agents working in sequence: Planner agents break down topics, Scout agents search academic databases, Signal agents evaluate paper relevance, Scribe agents write content, and Architect agents structure and format the output. This separation of concerns ensures each task is handled by a purpose-built agent.

Are the citations verified?

Yes, all citations are verified against real academic databases including Semantic Scholar (200M+ papers), CrossRef, and arXiv. Each source includes DOI links for independent verification. Unlike ChatGPT, OpenDraft cannot hallucinate citations because they come directly from database queries.

Yes, OpenDraft is 100% free and open source under the MIT license. You only pay for AI API usage (OpenAI or Google), which typically costs $2-5 per research draft. There are no subscription fees or usage limits.

How long does it take to generate a paper?

Generation time depends on complexity: research papers take about 10 minutes, bachelor's thesis drafts about 12 minutes, master's thesis drafts about 15 minutes, and PhD dissertation drafts about 20 minutes.

How does OpenDraft compare to ChatGPT for research?

ChatGPT frequently hallucinates academic citations (30-50% of generated citations are fabricated). OpenDraft's architecture makes this impossible because citations come from real database queries, not AI generation. OpenDraft is purpose-built for academic research with verified citations.

Can I submit OpenDraft papers as my own work?

OpenDraft generates drafts to help start your research. The output should be reviewed, fact-checked, edited in your own voice, enhanced with your original analysis, and used according to your institution's AI policy. Always check your university's guidelines on AI-assisted writing.

Does OpenDraft store my data?

No. OpenDraft runs entirely on your computer when self-hosted. Your research topics, generated papers, and API keys are never sent to external servers. You maintain complete control over your data and research.

What export formats does OpenDraft support?

OpenDraft exports to PDF, Word (.docx), and LaTeX formats. All exports include properly formatted citations in your chosen style (APA, MLA, Chicago, etc.).

Is OpenDraft suitable for PhD dissertations?

Yes, OpenDraft is designed to handle dissertation-length literature reviews and research drafts. The multi-agent system can process complex topics and generate extensive drafts with comprehensive citations from 200M+ academic papers.

Why is OpenDraft open source?

OpenDraft is open source (MIT license) for transparency, academic integrity, and customization. You can inspect exactly how citations are verified, how agents work, and modify the code for your needs. This matters for academic work where you need to explain your tools.

What databases does OpenDraft use for citations?

OpenDraft searches Semantic Scholar (200M+ papers), CrossRef (130M+ DOIs), and arXiv (2M+ preprints). This covers virtually all peer-reviewed academic literature across all disciplines.

How do I get started with OpenDraft?

Setup takes about 10 minutes: install Docker, clone the repository, add your OpenAI API key, and run the application. Detailed instructions are available in the GitHub repository's Quick Start guide.

Can I use OpenDraft for literature reviews?

Yes, literature reviews are one of OpenDraft's primary use cases. The multi-agent system excels at finding relevant papers, synthesizing findings, and creating comprehensive literature review drafts with verified citations.

Will my paper be flagged as AI-generated?

AI detection tools vary in accuracy. We recommend using OpenDraft as a starting point, then substantially editing the content in your own voice. OpenDraft generates drafts, not finished papers—your editing and original analysis are essential.

What AI models does OpenDraft use?

OpenDraft supports multiple AI providers including OpenAI (GPT-4), Google (Gemini), and Anthropic (Claude). You can choose based on your preference and API access. The multi-agent architecture works across all supported models.

OpenDraft AI

AI-Generated Draft

January 14, 2025

25 min read

Example

Example Draft: Zukunftsfähigkeit Optimierung eines Kleinteilelagers bei einem Kabelhersteller

German-language thesis generated by OpenDraft

This research paper was generated in 51.7 minutes with 23 verified academic citations from CrossRef and academic databases. Demonstrates multi-language support.

Generation Statistics

51.7

Minutes

Citations

~5K

Words

148KB

PDF Size

Download Draft

Download the complete draft in PDF or DOCX format:

Download PDF Download DOCX

Research Question (Forschungsfrage)

Wie kann ein Kleinteilelager in der Kabelindustrie zukunftsfähig optimiert werden, um den Anforderungen von Industrie 4.0 und steigender Marktdynamik gerecht zu werden?

(How can a small parts warehouse in the cable industry be optimized for the future to meet the demands of Industry 4.0 and increasing market dynamics?)

Abstract (Zusammenfassung)

Diese Forschungsarbeit untersucht die strategische Optimierung von Kleinteilelägern (KTL) in der Kabelfertigung unter besonderer Berücksichtigung der digitalen Transformation und Industrie 4.0. Die Analyse umfasst automatisierte Lagersysteme (AS/RS), Shuttle-Systeme, und die Integration von Warehouse Management Systemen (WMS).

(This research examines the strategic optimization of small parts warehouses in cable manufacturing with special consideration of digital transformation and Industry 4.0. The analysis covers automated storage and retrieval systems (AS/RS), shuttle systems, and warehouse management system (WMS) integration.)

Key Topics Covered

Lagerautomatisierung (Warehouse Automation)

AS/RS Systeme - Automated Storage and Retrieval System optimization
Shuttle vs. Miniload - Performance comparison of modern warehouse systems
Goods-to-Person - Efficient picking strategies for small parts
WMS Integration - Warehouse Management System architecture

Industrie 4.0 Integration

Digital Twin - Simulation and optimization of warehouse operations
IoT Sensors - Real-time monitoring and predictive maintenance
Machine Learning - Demand forecasting and inventory optimization
AGV/AMR - Autonomous guided vehicles in intralogistics

Kabelindustrie Spezifika (Cable Industry Specifics)

Varianten Management - High SKU variety handling
Sequence-dependent Setup - Production integration challenges
Heavy/Light Mix - Managing cable reels vs. small components

Citation Sample

All 23 citations in this thesis are verified against academic databases. Here are some examples:

Hosseini, S., et al. (2024). Deep Learning Techniques for Manufacturing-Warehouse Integration. Crossref.
Szpytko, J., et al. (2020). Exploitation Efficiency System of Crane based on RFID. IFAC-PapersOnLine.
Mutingi, M., et al. (2016). Genetic Algorithms for Order Picking Optimization. Industrial Engineering.
Vibbushitha, R., et al. (2025). Streamlining Inventory Management Strategies. Supply Chain Research.

Multi-Language Support

This example demonstrates OpenDraft's ability to generate academic content in German (and 57+ other languages). The system adapts academic conventions, citation styles, and terminology to the target language.

Want to generate your own thesis?

OpenDraft can generate research-quality academic drafts with verified citations in under an hour - in any of 57+ languages.Get started free