A systematic review can swallow a year. Two reviewers read every title and abstract, then read them again at full text. They extract data by hand, appraise risk of bias, resolve every disagreement, and log each decision so a peer reviewer can trace it. One large search can mean tens of thousands of records and hundreds of hours before synthesis even starts.
lets Review handles the heavy lifting without taking away your control. Multiple AI reviewers screen independently, then conflicts are adjudicated the way a third reviewer would. You set the criteria, check the calls, and keep the final say. Every action is logged. Speed never costs you rigor or reproducibility.
Set up your review for free. lets Review suggests your research question, review method, search matrix, subgroups, and extraction schema. You plan the method before the first search runs.
Multiple AI reviewers assess titles, abstracts, and full texts independently. You adjudicate only the conflicts.
Study characteristics, outcomes, and results into a structured, editable table, ready for analysis.
Appraise risk of bias, rate GRADE certainty, and build a PRISMA flow diagram that always matches your numbers.
Set up your review for free and get method suggestions: sharpen the research question, pick the right review format, build a search matrix, and define subgroups and an extraction schema. You start structured instead of rebuilding the protocol later.
Multiple AI reviewers screen each record independently against your inclusion criteria and flag disagreements for adjudication. Review the conflicts instead of reading 12,000 abstracts twice.
Included records move straight into full-text review. Each exclusion carries a logged reason. Your PRISMA exclusion counts and reasons are ready when you write the paper.
We launch a swarm of small agents that each hunt for the full-text papers you need to read. The few they can't find, you add yourself.
Pull study characteristics, outcomes, and results from full texts into a structured, editable table. Standardize fields across studies and export them clean.
Structured quality appraisal and GRADE certainty run in the same workflow. Judgments stay consistent across studies and reviewers.
Counts update as you screen. Your PRISMA 2020 flow diagram shows the real numbers at every stage. Build the synthesis on data that already matches the figure.
Every screening decision, exclusion reason, and extraction edit is timestamped and exportable. Hand a peer reviewer a complete, traceable record.
We have tested a range of AI models and adaptively pick the best one for each task, instead of relying on the judgment of a single model.
Create your review for free. Get suggestions for the research question, review method, search matrix, subgroups, and extraction schema, then adjust them.
Multiple AI reviewers screen titles and abstracts independently. lets Review shows you only the conflicts to adjudicate.
Move included studies to full text, extract data, appraise risk of bias and GRADE, and synthesize the evidence.
Download your PRISMA flow diagram, data tables, and audit trail as CSV, Excel, JSON, or Word.
| Capability | lets Review | Manual screening | General-purpose AI |
|---|---|---|---|
| Review planning & method | AI recommendations for question, search matrix, extraction schema | By hand or templates | Unstructured suggestions |
| Multiple independent reviewers | Multiple AI raters + adjudication | Two people, by hand | No structured second reviewer |
| Speed on large searches | Hours | Weeks to months | Fast but unstructured |
| PRISMA 2020 flow diagram | Built in, auto-counted | Manual, error-prone | Not generated |
| Risk of bias + GRADE | Built into the workflow | Separate tools / spreadsheets | Ad hoc, inconsistent |
| Data extraction to structured table | Yes, editable | Manual | Unstructured text |
| Audit trail / reproducibility | Complete, timestamped | Depends on notes | None |
| Methodological control | You set rules and decide | Full | Hard to constrain |
| Exports (CSV / Excel / JSON / Word) | Yes | Manual | Copy-paste |
Compares lets Review against manual screening and general-purpose AI chatbots. For a verified, feature-by-feature comparison against named platforms, add a separate, dated table once you have testable results.
Yes. Set up your review for free and get suggestions for the research question, review method, search matrix, subgroups, and extraction schema. You plan the method early and run it in the same tool, and you adjust every suggestion and keep methodological control.
AI handles the time-consuming stages: title and abstract screening, full-text screening, data extraction, and appraisal. lets Review uses multiple independent AI reviewers plus adjudication, while you set the criteria and make the final calls. You can prepare the planning in the tool too. The method stays yours.
Accuracy depends on the workflow. lets Review runs multiple AI reviewers independently and routes every disagreement to human adjudication. The AI is conservative by design and flags records for review rather than excluding them silently. [ Add your benchmark or agreement figure once verified. ]
It depends on the number of records and your criteria, but stages that normally take weeks often drop to hours. lets Review removes the duplicate manual reading and the rebuilding of logs. Most of the saved time comes from screening and data extraction.
lets Review is free to set up and plan, and your first 50 records are free too. After that, pricing is simple and per review, with no long contract. You can plan the method and test a small review before paying. [ Insert current per-review price or pricing-page link here. ]
You define inclusion and exclusion criteria. Multiple AI reviewers read each title and abstract independently and label it include or exclude. Where they disagree, lets Review routes the record to you. Every call is logged with a reason for your PRISMA report.
Yes. lets Review pulls study characteristics, outcomes, and results from full texts into a structured, editable table. You standardize fields across studies and export to Excel, CSV, JSON, or Word, ready for synthesis or meta-analysis. You can correct any extracted value.
lets Review mimics multiple independent reviewers plus adjudication, but you control the criteria and the final decisions. Treat it as AI-assisted screening that lowers the manual load, not an unsupervised replacement. Check your discipline's and journal's guidance on AI use.
Yes. lets Review counts your records at every stage and generates a PRISMA 2020 flow diagram that matches them. You export the diagram alongside your data tables and audit trail as CSV, Excel, JSON, or Word. Figure and numbers always agree.
Plan, screen, extract, and synthesize in one place, with an audit trail you can defend.
lets Review