A structured literature review, with every source verified.
Build a structured review table with the columns your review needs, method, sample, findings, whatever you extract, and every source checked against CrossRef and Semantic Scholar as it lands. Screen, tag, sort, and export to BibTeX, RIS, or CSV. You do the reading and the judging. CoChat does the structure and the checking.
Free to start. You decide what is included. CoChat structures, verifies, and exports.
What is an AI literature review in CoChat?
The manual way is a spreadsheet with forty columns that no two co-authors fill in the same way, references pasted from four databases, and no way to know if a citation is even real until a reviewer catches it. The review is only as trustworthy as the least careful row.
CoChat replaces that with a live artifact. Papers you include become rows. The details you care about become columns. Verification runs in the background, so the table you build your argument on is structured and checked from the first row, not audited at the end.
From included papers to a finished table
The table is the backbone of the review,
not a side artifact.
A literature review table is rarely the deliverable on its own. It is what the rest of the work is built on.
The sources you include here are the ones you cite when you draft, already verified, so the reference list writes itself clean. The columns you extract become the synthesis and the evidence table in your manuscript. The screening decisions you record become your PRISMA counts. And because the table lives in the same workspace as your search, your Library, and your citations, nothing is re-entered and nothing drifts. You build the review once and everything downstream draws from it.
One review, structured and verified
A spreadsheet vs. a verified review table
The manual spreadsheet
CoChat literature review
Getting sources in
Paste from four databases, reformat by hand
Search or pull from your Library, screen in
Trust
Hope every reference is real
Every source checked against CrossRef and Semantic Scholar
Extraction
Forty columns, filled inconsistently
Custom columns, drafted for you to review
Finding a subset
Scroll, filter, lose your place
Tag, sort, and filter in one click
Consistency
Version_final_v3_REAL.xlsx
| One live artifact, always current |
Export
Reformat citations again
BibTeX, RIS, or CSV, no lock-in
CoChat builds the review on checked sources, not trust.
A reference manager stores what you give it. A spreadsheet holds whatever you type. Neither asks whether a source is real, whether the metadata is right, or whether the paper supports the claim you attached to it, and that gap is exactly where a review loses its footing.
CoChat verifies every source against CrossRef and Semantic Scholar as it enters the table, so the evidence base under your synthesis is checked from the start. And because the table lives in the same workspace where you search, screen, verify, and cite, the review you build here is not a document you export and abandon. It feeds your citations, your PRISMA counts, and your draft, and it stays in your Library to build on for the next project. The more you use it, the less you rebuild.
Same table, different research
Same capability, different context. See how the literature review works across fields and roles.
Frequently asked questions
1. What is an AI literature review tool?
2. Does CoChat write my literature review for me?
3. Which databases can I build a review from?
4. Can I choose my own extraction columns?
5. Can I export the review to my reference manager?
6. How is this different from a reference manager?
Build the review once. Everything else draws from it.
Search or import your sources, screen what belongs, extract into your own columns, and export a verified bibliography, all in one workspace.
Free to start. You decide what is included. CoChat structures, verifies, and exports.