AI-assisted writing and storytelling
Image generation with Anime Art AI and other models
Customizable AI modules for specific themes and styles
Lorebook for world-building and AI consistency
Text Adventure Module for interactive storytelling
Rayyan, Seamless, DistillerSR, ResearchBuddy, Elicit, RatingHub, AI-powered Scientific Review Generator, Cambrian, NovelAI, Review Insights Pro are the best paid / free ai assisted literature review tools.






AI-assisted literature review is a process that leverages artificial intelligence and machine learning techniques to streamline and enhance the traditional literature review process. It involves using AI algorithms to search, screen, and analyze large volumes of research papers and publications, helping researchers identify relevant studies, extract key information, and synthesize findings more efficiently and effectively.
Core Features
|
Price
|
How to use
| |
|---|---|---|---|
NovelAI | AI-assisted writing and storytelling |
Paper Free Trial The AI Access to Kayra, our top of the line AI Storyteller. 100 Free Text Generations* 6144 Tokens of Memory. 100 Free TTS Generations.
| Users subscribe to a monthly plan to access NovelAI's AI-powered writing and image generation tools. They can then input text prompts to generate stories, customize the AI's output, and create images based on their descriptions. |
Elicit | AI-enabled systematic reviews |
Basic Free For casual exploration
| Use Elicit by asking research questions in natural language. The AI will search, summarize, extract data, and chat with over 125 million papers to provide answers and insights. |
Rayyan | AI-powered screening | Rayyan allows users to import research data from tools like Mendeley, Zotero, EndNote, and PubMed. Users can then utilize AI-powered screening, deduplication, filters, and bulk actions to efficiently manage and accelerate their reviews. The platform also supports team collaboration and offers customizable workbench features. | |
DistillerSR | AI-enabled literature review automation |
Student $19.95/month (Three subscriptions for the price of one)
| The DistillerSR platform automates the conduct and management of literature reviews. Its configurable, AI-enabled workflow streamlines the entire literature review lifecycle, allowing users to make informed evidence-based decisions. |
Cambrian | Search over 240,000 ML papers | Use Cambrian to search over 240,000 ML papers, discover the latest research, understand confusing details, and automate literature reviews. | |
ResearchBuddy | Automatic literature review generation | Sign up for a free account, then use the app to create new reviews. The app streamlines the research process and presents relevant information. | |
Review Insights Pro | AI-powered sentiment analysis |
FREE TRIAL $0.00 1 User, 1 Week, Unlimited use
| Use the app or Chrome extension to manage and analyze customer reviews, gain insights, and craft professional responses. |
AI-powered Scientific Review Generator | AI-powered scientific review generation | The website reads hundreds of scientific papers and automatically generates a review in minutes. | |
RatingHub | Multi-channel review syncing | Standard $25 per business / month Unlimited user accounts, unlimited reviews, unlimited channels, advanced reviews filtering, data reporting, multi-channel QR landing page, AI weekly digest, AI response writer | Start a free trial to gather and analyze reviews from multiple channels. The platform automatically syncs reviews, provides performance tracking, and offers AI-driven insights. Use the interactive charting and review filtering tools for deeper customer insight. Collect reviews through a dedicated landing page using a link or QR code. |
Seamless | AI-Powered Literature Review |
10 Credits $9.99 10 literature reviews
| Users can input a paper description, and Seamless will generate a literature review based on real papers from the Semantic Scholar database. For scholarship applications, the tool provides AI-powered suggestions for essay structure and content, real-time feedback, and language enhancement. |
In the biomedical field, AI-assisted literature review is used to expedite evidence synthesis for clinical guidelines and drug discovery
In the social sciences, it is applied to map out research trends, identify knowledge gaps, and inform policy decisions
In the business domain, it is used for competitive intelligence, technology landscaping, and patent analysis
User reviews of AI-assisted literature review tools are generally positive, with many praising their time-saving and efficiency benefits. Some users appreciate the ability to customize search strategies and screening criteria, while others find the visualization features helpful for exploring and interpreting the data. However, some reviewers note that there is a learning curve associated with using these tools, and that they may not be suitable for all types of literature reviews. Overall, users recommend carefully evaluating different tools and their capabilities to find the best fit for a given research project.
A graduate student uses an AI-powered tool to quickly identify and summarize key papers for their thesis literature review
A research team applies machine learning to screen thousands of abstracts and full-text articles for a systematic review on a medical topic
A policy analyst leverages sentiment analysis to gauge public opinion on a controversial issue based on online news articles and social media posts
To implement AI-assisted literature review, researchers typically follow these steps: 1) Define the research question and search strategy, 2) Select appropriate databases and AI tools, 3) Train the AI models on a subset of manually reviewed papers, 4) Run the AI algorithms to search, screen, and analyze the literature, 5) Validate and refine the results through human review, 6) Synthesize the findings and draw conclusions. Prerequisites include access to research databases, programming skills (e.g., Python), and familiarity with AI/ML concepts.
Saves time and effort in searching and screening large volumes of literature
Improves the accuracy and consistency of study selection and data extraction
Enables discovery of new insights and patterns through text mining and data visualization
Facilitates collaboration and reproducibility by providing a transparent and systematic approach
Allows researchers to keep up with the rapidly growing body of scientific literature







































