Qinyan Academic: An AI Research Assistant Covering the Full Path from Topic Selection to Publication

Qinyan Academic is a full-path AI research assistant for researchers, covering topic selection, literature search, academic writing and publication. Research work is naturally fragmented: finding papers happens on search platforms, reading them relies on PDFs and notes, writing a paper happens in a document tool, and building a presentation uses yet another set of software. Connecting these stages usually means repeatedly moving material between tools and manually aligning formats. Qinyan Academic takes a different approach by bringing them into one platform — an AI super agent, a personal knowledge base, AI agent capabilities and team collaboration are all included, together with concrete functions such as literature download, academic Q&A, review generation, AI presentation generation and patent search. It also has one design choice that is especially practical for long-running research: a memory function that keeps track of the research over time.

Main Features

End-to-end literature workflow Covers search, download, reading, academic Q&A and literature review. The literature job is broken into these five stages and handled separately, instead of only solving the "find it" part.

AI topic selection and frontier insight Focuses on recommending topics based on academic hotspots, and continuously tracks disciplinary frontier developments and research trends. It is useful as a reference when judging direction at the early stage of a project.

Smart writing Provides one-stop writing and publication support with outline generation, paper writing, polishing, translation and AI presentation generation. From structure to draft to polish to submission materials, the writing stage is covered continuously.

Deep research Can generate research reports, run data analysis, build mind maps and support research design, assisting research decisions. Mind-map structuring is especially useful for organizing a research framework.

Research resource management A knowledge base paired with an AI cloud drive lets you upload your own literature material to build a dedicated knowledge base and manage research files centrally in the cloud. This item determines whether answers are based on your own material rather than general knowledge.

Agent and collaboration The QinyanClaw agent can autonomously execute complex research tasks; "My Group" supports team collaboration and group project management, aimed at research group scenarios.

How to Use

1. Register and log in: Create an account and sign in through the product site; a desktop client and a browser extension are available for download.
2. Enter the agent: After logging in you land on the research super agent page by default, and can switch between "Smart Mode" and an expert-panel mode oriented to AI for Science scenarios.
3. Build a knowledge base (optional): Upload your own literature material so the AI answers from your dedicated sources. This step has a large effect on answer quality.
4. Choose an entry point: Depending on your need, pick a task from the three main scenarios: research preparation, writing and publication, or research assistance.
5. Start a conversation: Describe what you need in the input box using natural language.
6. Call tools: Inside the conversation you can attach a knowledge base, generate images, run data analysis, or use dedicated tools directly, such as topic selection, search and presentation generation.
7. Iterate and refine: Use the memory function to hold multi-turn conversations and keep revising the generated content.
8. Export results: Export and save the final literature review, paper or presentation, or share it with your team through "My Group".

Core Advantages

• Full-process coverage: Topic selection, literature, writing and publication handled in one place, without switching between tools
• Full-path AI agent: The research super agent and the QinyanClaw agent can plan and execute complex research tasks autonomously
• Memory function: Remembers conversation context and knowledge base content over time, so research follow-up does not go blank
• High-hit-rate literature download: Officially stated to support one-click batch download of more than 95% of literature
• Personal knowledge base: After you upload your own material, the AI answers based on your research files
• Efficiency figures, as officially stated: Officially published numbers are 60% shorter topic-selection cycles, 80% less search time and 70% higher review efficiency (platform figures, not third-party verified)
• AI4S expert panel mode: Provides professional-grade depth for AI for Science and scientific computing scenarios

Differences from Similar Tools

Similar research-oriented AI tools usually position themselves as a "dedicated AI research colleague" or a "full-cycle research orchestration system". They tend to emphasize autonomous experiment execution, self-monitoring and self-repair, turning raw data into a paper draft in one step, and connecting to laboratory automation equipment; their literature capabilities lean toward deep analysis, automatically extracting arguments, methods and key data.

Qinyan Academic makes different trade-offs at both ends. First, it completes the literature stage — search, download, reading, Q&A and review each have a corresponding function. Second, it completes the writing stage — outlines, writing, polishing, translation, review and AI presentation are all included, plus a personal knowledge base and team collaboration. It does not provide experiment execution or hardware integration; its position is before the experiment and before publication.

The way writing support is delivered differs too: similar tools lean toward turning raw data into a draft in one step, whereas Qinyan Academic offers assistance stage by stage, including one-click insertion of literature citations and smart polishing.

Applicable Scenarios

• Academic research and literature organization: Collect, classify and organize literature at the early stage of a project, using cloud storage and tagging to structure material
• Deep reading and analysis of literature: Use AI close reading, note mind maps and literature analysis tools to extract core content, generate mind maps, and understand a paper's logic and research value
• Academic writing and polishing: Insert literature citations, polish text intelligently and expand content precisely while drafting a paper
• Team collaboration and project management: Sync writing content in real time and share literature material within team research projects
• Academic reporting and presentation: Generate reporting presentations with note mind maps and AI tools, and improve delivery with real-time Q&A

Limitations and Cautions

• AI-generated literature summaries, reviews and paper content may contain citation errors and factual deviations; every citation and figure must be checked line by line before submission.
• The automatic literature citation insertion feature carries a mismatch risk; whether a citation points to the correct paper needs human confirmation.
• "More than 95% literature download" and the efficiency improvement figures are official platform claims; actual results depend on discipline, search strategy and how you use it.
• Materials in your personal knowledge base are uploaded to the cloud; when unpublished research data is involved, confirm data security and confidentiality requirements in advance.
• There is no experiment execution or hardware integration capability, so laboratory-stage work still depends on specialist tools and lab conditions.
• Use must follow the academic norms of your institution and the platform's service terms.