GenAI Research Assistants

These tools are true Generative AI tools. They use large language models (LLMs) to:

• Summarise abstracts, papers, or specific sections.
• Generate answers to questions based on academic literature.
• Extract key information (e.g., methods, sample sizes, results) into structured tables.
• Explain difficult text in plain English.

They generate responses based on patterns in their underlying datasets — often derived from indexed academic sources — rather than retrieving content from the live web.

Most are built on open datasets like Semantic Scholar or OpenAlex, meaning they may miss paywalled content or papers outside those collections.

Always check their coverage limits, and verify any outputs using proper academic sources.

Here are some widely used tools, each with different strengths and limitations:

Elicit

• What it does: Answers research questions, summarises papers, and builds evidence tables from the Semantic Scholar corpus.
• Data source: Searches 125M+ papers from Semantic Scholar; uses full text where available.
• Limits: Coverage restricted to Semantic Scholar data; misses many paywalled sources.
• Best for: Generating quick summaries of research findings or comparing study methods.
• Standout feature: Table builder that extracts key variables (e.g., sample size, outcome measures) from listed papers.
• Freemium model: Free with limits on queries and extracted results; paid unlocks larger tables and advanced features.
• Website: elicit.com

Consensus

• What it does: Answers yes/no style research questions using summaries generated from academic literature.
• Data source: Corpus blends Semantic Scholar, OpenAlex, and a proprietary scholarly crawl (200M+ docs).
• Limits: Relies on open datasets; misses paywalled content.
• Best for: Quick answers to questions like “Does X affect Y?” based on published research.
• Standout feature: Shows how many papers support, refute, or are neutral on a given question.
• Freemium model: Free for a limited number of queries; premium unlocks more questions, deeper summaries, and citations.
• Website: consensus.app

Scite Assistant

• What it does: Uses AI to summarise research claims, show how papers cite each other (supporting, contrasting, or mentioning), and answer questions.
• Data source: Smart Citations from full-text contexts; coverage expanded via publisher partnerships
• Limits: Only partial coverage; advanced features require payment.
• Best for: Understanding citation context and summarising claims across multiple papers.
• Standout feature: Smart citation classifications (support, contrast, mention) plus a chat-based assistant.
• Freemium model: Free trial (7 days); paid plans unlock full Smart Citations and Assistant features.
• Website: scite.ai

Tip: Not sure how these tools compare to other academic search tools like LibrarySearch or Web of Science? Visit our Search and Discovery Tools page to learn how different search tools work — and when to use each one.

Tip: These tools are helpful for summarising and exploring research — but they don’t replace full academic searches. Check the Search and Discovery Tools page to choose the best academic search engine for your topic.

Many AI research assistants use a freemium model. The free versions allow a limited number of summaries, queries, or extractions. Paid versions unlock larger tables, unlimited questions, or faster processing.

You do not need to pay to succeed. Everything you need for your studies can be done using the free features of these tools, plus the academic resources provided by the Library.

These tools do not search the entire academic universe. Most rely on open datasets like Semantic Scholar, OpenAlex, or Crossref. This means:

• They may miss paywalled content (e.g., papers in Elsevier, Wiley, Springer, or Taylor & Francis journals).
• Depending on the tool, outputs may rely on abstracts when full text isn’t available (e.g., Elicit uses full text when it can; scite’s ‘Smart Citations’ come from full-text citation contexts).
• Results may be stronger in some fields (STEM, psychology, computer science) and weaker in others (humanities, law, creative industries).

Important: Do not upload unpublished research, identifiable participant data, or grant applications. Always check that you have the rights to share any PDF you upload.

Generative AI research assistant search results are not fully reproducible.

• Two users may get different summaries or answers from the same question.
• These tools rely on dynamic AI models, changing training data, and algorithm updates.
• Outputs may be inconsistent and cannot replace reproducible search strategies.

Tip: If you're using one of these tools for scoping or summaries, note the date, the query you used, and what corpus the tool is drawing from.

These tools are helpful for summarise and explore  — but they do not replace:

• Formal literature review methods (systematic searching, PRISMA, etc.)
• Critical reading of full papers
• Verification of peer-reviewed status
• Evaluation of source credibility

See: Evaluating AI-Generated Content for guidance on checking whether GenAI-generated answers are reliable.