Choose between Elicit AI, Consensus, SciSpace and AnswerThis by testing the work your literature review requires. Use the same question and papers in each tool, then follow the evidence from the search to export. Compare the sources you find, the claims you can verify and the extracted information you can use alongside each tool provider's promises.

Start with the research task, not the paper count

A literature review begins with a question, but it does not end with a list of papers. You need to read the studies, check what they support and bring the evidence together. The four tools describe different starting points for that work.

AnswerThis

AnswerThis describes itself as an “AI Research Assistant for Literature Reviews.” Its recorded description says its search covers more than 250 million papers. Test whether it finds the papers relevant to your field and question, just as you would with another tool provider’s coverage claim. Source: AnswerThis.

Elicit

Elicit describes itself as “AI for Scientific Research.” The recorded description says users can search more than 138 million academic papers and 545,000 clinical trials. These are tool provider-reported coverage figures, not independently tested results. Source: Elicit.

Consensus

Consensus describes itself as “an AI academic search engine for peer-reviewed literature.” That tells you which material it emphasizes. It does not show whether the tool finds all relevant studies or interprets them correctly. Source: Consensus.

SciSpace

SciSpace describes itself as “the AI research assistant for academics.” Its recorded description says users can “Run systematic literature reviews on 280M+ papers, and write papers with cited sources.” This describes the intended functions. It does not establish that a generated review meets your research protocol. Source: SciSpace.

Finding papers, explaining methods, extracting published results and analyzing an original dataset are different tasks. A broad product description does not establish that a tool handles each task well.

Follow one literature review through all four tools

Choose one research question and a set of familiar papers, then follow them from discovery to export in each tool. Keep the results in one sheet so you can compare what happened at each stage. This turns the tool providers' descriptions into a test you can check against sources you already know.

1. Does it find the papers you need?

Begin with the search. Define your question and scope, then select familiar papers with different research methods and publication types. Search for each paper by title before running the same topic search in all four tools.

The familiar papers give you a reference point: you can see which studies a tool misses and which irrelevant results it adds. Compare the results with the library databases appropriate for your field, and check whether each result gives you the full text or only an abstract.

A large advertised collection does not prove complete coverage. A tool can list a paper without providing its full text.

For cross-disciplinary work, test the terms used in each field. Good results in one field do not establish good coverage in another. Record bibliographic entries, abstracts and available full texts separately.

2. Do the cited passages support the answers?

Once you've found the papers, check how accurately each tool represents them. Ask the same questions about the same studies in all four tools, then open every citation attached to a claim you plan to use.

Find the supporting passage and compare its population, method, outcome and stated limits with the generated answer. Check numbers, units, direction and time points. Record any changed meaning, unsupported detail or missing qualification. Then ask something the paper doesn't answer and check whether the tool acknowledges the gap.

A citation identifies a source. It does not prove that the source supports the sentence. An answer that says one factor causes another needs stronger support than a paper that reports an association.

Keep the original quotation and its location beside your notes. That lets you or another reviewer return to the evidence.

3. Does it extract the right information?

A checked summary is useful, but a literature review also needs evidence you can compare across studies. This is where data extraction comes in: recording information reported in a paper, rather than calculating a new result or analyzing an original dataset.

Define the fields your review needs before testing. These might include sample characteristics, theories, methods, measures, findings or limitations. Build a reference sheet by checking the familiar papers yourself, then ask each tool to extract the same fields.

Compare every value with your reference sheet and record incorrect entries, missing values and source locations. Another reader should be able to trace each entry back to the paper without guessing how you obtained it.

Distinguish “not reported in the paper” from “not found by the tool.” Do not treat an empty result as proof that the authors omitted the information.

If you also need calculations, test them separately. Require enough detail to reproduce the calculation and check the inputs.

For more on search, extraction and screening, see AnswerThis vs Elicit. Check plan-specific claims against each tool provider’s current documentation.

4. What happens to uploaded documents?

Before extending that test to your own documents, check whether you are allowed to upload them. A tool's usefulness does not establish that its data policies fit your project. Begin with public papers you have permission to upload, not confidential material.

Check the terms that apply to your account:

• Retention: How long does the service keep files and results?

• Deletion: What happens when you delete a file?

• Model training: Can the service use your content to train models?

• Third-party processing: Which other providers receive the content?

• Permissions: Do institutional rules, contracts, or participant agreements allow the upload?

Owning a copy of a document does not necessarily give you permission to send it to a service. Keep confidential manuscripts, identifiable participant data and restricted datasets out of the test until you resolve permission questions. 

5. Does the plan support your whole workflow?

Follow the evidence out of the tool by exporting references, notes and tables. You need to know whether those files preserve what you'll use in the next stage of the review. An on-screen answer alone won't show you that.

Open the exported files and inspect them for missing citations, values or source locations. Confirm that the formats fit your existing research tools. Then check the specific plan's usage limits and billing commitments, including whether it covers the search, reading, extraction or screening tasks you just tested.

A tool is not a good fit if you cannot use its output in the next stage of your work. Resolve cost and export questions before subscribing.

For a comparison of question-answering workflows, see AnswerThis vs Consensus.

Bring the comparison back to the evidence

Your test notes show how each tool handled the papers you supplied. Compare those observations with the recorded tool provider claims below, keeping the two kinds of evidence separate. The table summarizes advertised scope and the tasks to test. It doesn't score performance.

Evidence snapshot: September 30, 2026. The table summarizes recorded tool provider descriptions. It does not report an independent performance test or guarantee current plan terms.

Tool: Elicit
Tool provider’s stated focus: Scientific research
Advertised coverage: More than 138 million papers and 545,000 clinical trials
What to test: Paper discovery, extraction, plan limits and exports

Tool: Consensus
Tool provider’s stated focus: Academic search of peer-reviewed literature
Advertised coverage: No total established in the supplied evidence
What to test: Whether passages support answers and preserve qualifications

Tool: SciSpace
Tool provider’s stated focus: Research assistance for academics
Advertised coverage: More than 280 million papers
What to test: Paper explanations and review tasks against your protocol

Tool: AnswerThis
Tool provider’s stated focus: Literature review research assistance
Advertised coverage: More than 250 million papers
What to test: Discovery, cited answers, extraction and exported evidence

Confirm: Current comparable costs, account-specific upload policies, retention and deletion terms, model-training rules, usage limits and export options. Use the tool provider’s own documentation to resolve the gap, rather than another tool provider’s comparison page.

Decide which part of your review needs help

Use your test notes to choose a tool for the work you intend to give it. A tool that helps you find papers may need a separate test for extraction or analysis. Focus the decision on the part of your review where you need help.

Finding relevant studies

Compare relevant results, missed papers and access to the underlying sources. An Elicit vs Consensus comparison is useful when you test the same question, not when you seek a winner for every subject.

Reading papers you already have

Check explanations against the exact passage. Include difficult methods sections and ask questions that expose missing evidence. See AnswerThis vs SciSpace for a comparison covering cited literature reviews and PDF chat.

Screening and extracting studies

For a systematic review, test whether you can apply your inclusion rules, inspect screening decisions and trace extracted values to sources. A systematic-review label does not establish that the software meets your protocol.

Analyzing data

State exactly what you mean: extracting published findings, combining results across studies or analyzing an original dataset. These jobs require different tests. Search and chat features do not establish that calculations or analyses are valid.

Keep the same test notes for every candidate. Compare errors, corrections and usable exports. Choose based on what you checked, not how confident an answer sounds.

Carry the source checks into your final review

Choosing a tool does not end the verification work. The same passage checks you used during the comparison belong in the final review, wherever you retain an AI-assisted claim.

Harvard Library warns: “Generative AI is NOT a research database.” Check generated content against original papers and the scholarly records available through appropriate library resources.

Walters and Wilder’s 2023 study in Scientific Reports examined 636 citations generated by GPT-3.5 and GPT-4. It found fabricated citations in 55% and 18%, respectively. Among real citations, 43% and 24% contained substantive errors.

For every claim you retain, check both the reference and the passage. Record the tool, prompts, documents, outputs used and corrections made.

Follow your institution’s and publication’s disclosure rules. State whether AI helped with discovery, summarization, extraction or another task. You remain responsible for the evidence and interpretation.

Choose the tool that leaves you with evidence you can check and use. Follow that evidence from search to export, noting errors, corrections and usable outputs along the way. That gives you a reason for your choice grounded in your review's needs. A confident answer or a large advertised paper collection can't substitute for those checks.

FAQs

What is the difference between Elicit and Consensus?

Elicit describes a scientific research focus, while Consensus describes an academic search engine for peer-reviewed literature. Test the same question and familiar papers in both. Compare source access, supporting passages, outputs and plan limits.

Which is the best AI tool for research?

The best AI tool for your research is the one that handles your literature-review tasks with evidence you can verify and outputs you can use. Test Elicit, Consensus, SciSpace and AnswerThis with the same questions and papers, comparing discovery, source support, extraction and exports. Also check upload permissions and plan limits before choosing.

How should I choose an AI research assistant for a dissertation?

Test the tasks your dissertation requires using papers you can check yourself. Compare discovery, summaries, extraction and citations, then confirm upload permissions, exports and cost. Follow your institution’s AI-use and disclosure rules.

Author bio: Dr. Rajni Garg is Executive Lead, Research & Content Strategy, in the Research & Development Department at AnswerThis, a research platform for students and researchers.