AI Research
Free
AI Research is suitable for individuals and teams to quickly verify and implement.
AIResearch
Core parameters and statistics
| Project | Specifications |
|---|---|
| Product Name | AI Research |
| Category | AI Academic Research |
| Delivery form | Web/SaaS |
| Support Platform | Web |
| Supported languages | Chinese, English |
| Target users | Graduate students and scholars, scientific research teams, scientific research managers |
| User scale | Undisclosed |
| Pricing Model | Freemium / Subscription |
Platform coverage and user scale data are based on the official real-time page and third-party statistics.
User and market recognition
Gradually build user awareness in the field, and product capabilities are used by content creators and teams to improve work efficiency. Some industry users have incorporated it into their daily workflow. It is recommended to refer to the latest official disclosures for specific user scale and industry adoption rate data.
Cost advantage
| Cost Dimension | Description |
|---|---|
| Free version | Basic semantic search + 30 paper analysis per month + basic trend tracking |
| Subscription version | Unlimited paper analysis + in-depth trend analysis + citation export, $15/month |
| Enterprise Edition | Team collaboration + shared library + SSO + management backend, business pricing |
Compared with traditional manual literature research (8-15 hours at a time), using AI Research can compress literature screening to 1-3 hours, improving efficiency by about 5 times.
Main functions
- Semantic Literature Retrieval: A paper retrieval engine based on natural language semantic understanding, supporting research questions/method names/experiment description queries, covering arXiv, Semantic Scholar, DBLP, etc. Applicable tasks: quickly locate relevant papers; usage value: upgrade from keyword matching to semantic understanding.
- Structured paper analysis: Upload PDF to automatically extract research questions, methodological framework, experimental settings and core conclusions. Applicable tasks: speed reading of papers; value of use: traditional reading from 30-60 minutes is reduced to 1-2 minutes.
- Research Trend Tracking: After setting the direction of attention, continue to track new papers and changes in hot topics, combined with citation networks and keyword popularity. Applicable tasks: tracking cutting-edge developments; value of use: avoiding missing important progress.
- Citation Management and Export: Supports BibTeX and RIS formats, and automatically adds structured information (method labels, data sets) when exporting. Applicable tasks: literature compilation; use value: improving the efficiency of citation management.
- Literature Notes and Collaboration: Supports personal notes and tags, which can be selectively shared to form collective knowledge accumulation. Applicable tasks: team knowledge management; value of use: information consistency for collaborative research.
Model and version evolution
| Version | Date | Key Changes |
|---|---|---|
| Latest version v1.0 | 2026-07 | Paper structured analysis engine, trend tracking module, citation management, PDF parsing upgrade |
| Previous version v0.9 | — | Basic semantic retrieval and PDF parsing, covering arXiv and some open access papers |
The version record shall be subject to the official release notes.
Technical advantages
- Domain Vertical Semantic Retrieval Engine: Based on fine-tuning of paper corpus in the AI field and training on millions of papers in the arXiv cs.* subset, its understanding of AI terms is better than that of general search engines.
- Unstructured PDF structured pipeline: layout analysis → text extraction → semantic role annotation → structured output pipeline, each module can be optimized independently.
- Trend analysis combining citation network and text mining: Using both citation relationships (quantitative) and semantic changes (qualitative), dual-signal judgment is more accurate than single dimension.
- Security and Compliance: The SaaS architecture is continuously updated, paper analysis data is only used for the current request, and storage and deletion policies are guaranteed after the PDF is uploaded.
How to use
| Entrance | How to use |
|---|---|
| Web side | Visit the official website with a browser → Search papers → Browse analysis tags → Upload PDF to obtain interpretation → Set up tracking |
Typical usage process: Enter a research question → Browse semantic search results → Select a paper to obtain a structured interpretation → Add to favorites → Set up trend tracking.
Product Pricing
| Package | Price | Contents |
|---|---|---|
| Free version | $0 | Basic semantic search + 30 paper analysis per month |
| Premium | $15/month | Unlimited analysis + in-depth trends + quote export |
| Institutional Edition | Business Pricing | Team Collaboration + SSO + Management Backend |
Pricing. There are different pricing in different regions.
Application scenarios
- Project Literature Research: Traditionally 2-4 weeks to read 50-100 papers, use structured analysis to compress the preliminary screening to 3-5 days. Verification method: Analyze the consistency between the research context of automatic identification of method labels and manual judgment.
- Daily Paper Tracking: From manually browsing arXiv for 30-60 minutes per day to 15-20 minutes per week. Verification method: Missing rate of key papers in push results.
- Interdisciplinary Rapid Learning: Establishing knowledge framework shortened from 2-3 weeks to 3-5 days. Verification method: Core paper coverage.
Applicable people
- Individual users: Postgraduate students and scientific researchers who need to improve the efficiency of literature research
- SME Team: Research groups and laboratories need collaborative document management
- Large Enterprises: Enterprise AI labs require trend tracking and competitive product method analysis
- Not suitable for boundaries: non-AI/ML field disciplines, core papers that require in-depth reading, and interdisciplinary research needs
Comparison of competing products
| Comparative Dimensions | AI Research | Google Scholar | Semantic Scholar |
|---|---|---|---|
| Core differences | Structured analysis depth | Search breadth | Citation network |
| Price | Freemium | Free | Free |
| Coverage scenarios | Retrieval + analysis + tracking + citation | Retrieval + citation | Retrieval + citation network |
| User reviews | Good depth of analysis, only in the AI field | Comprehensive coverage | Good citation analysis |
| Technical threshold | Low | Low | Low |
Summary and Outlook
AI Research offers a valuable combination of capabilities for literature analysis in the AI vertical - integrating retrieval, structured analysis, trend tracking and citation management in a single workflow. The core difference is "depth of analysis" rather than "breadth of search". It is recommended to pay attention to its function iteration speed, pricing strategy changes and ecological expansion direction. It is suitable to use the free version to experience it first and confirm the matching before making an investment decision.
Risk Disclosure: The accuracy of structured analysis of the paper is between 70% and 85%, and it cannot completely replace manual reading; the extraction results should be regarded as "auxiliary reading notes" rather than replacing the original paper. Only covering the field of AI cannot meet the needs of interdisciplinary researchers. Preprint version tracking is not supported yet. Enterprise users need to confirm the feasibility and cost of privatized deployment. Verification of key conclusions, experimental data and methodological details must return to the full text of the original paper.
Related tools: crewai, langchain
Version Info
- Public beta version ：It is currently a publicly accessible version, and specific functions will be updated at a specific pace.
- earlier version ：An early trial version, the core direction is consistent with the current version.
User Reviews