A multi-agent AI system that researches, outlines, drafts, and reviews scholarly theses — then exports them as publication-ready PDF, Word, or LaTeX documents.
Each agent handles a distinct phase of thesis writing — coordinated by a pipeline orchestrator that manages retries, progress tracking, and phase transitions.
Searches Semantic Scholar and arXiv via Tavily, ranks sources by relevance, extracts structured metadata, and embeds content into vector memory for retrieval.
Generates a structured outline, then drafts each section with inline citations, vector-grounded context, and word count validation. Saves incrementally so partial progress survives failures.
Reviews each draft section for argument gaps, weak evidence, missing citations, and style issues. Generates specific suggestions you can accept or reject.
Generic LLMs hallucinate citations and produce unstructured output. Our specialized agents are purpose-built for academic writing.
| Capability | Standard LLMs | ThesisAI |
|---|---|---|
| Live Source Discovery | Training data only | Semantic Scholar & arXiv |
| Thesis Structure | Unreliable | 6-section academic outline |
| Source-backed Citations | Hallucinated | Linked to real sources |
| Export Formats | Plain text | PDF, Word & LaTeX |
| Quality Review | None | Critic Agent review |
How It Works
From your first research question to a fully cited, export-ready document — our AI agents handle the heavy lifting while you stay in control.
Enter your thesis title, description, academic level, and citation style. That's all we need to get started.
Our agents search Semantic Scholar and arXiv, rank sources by relevance, and build a structured literature base.
The Writer Agent drafts each section with inline citations. The Critic Agent then reviews for gaps, logic, and style.
Export as a formatted PDF, Word document, or LaTeX file — complete with table of contents and bibliography.