For PhD Students & Early-Career Researchers

Your literature review, done properly

PRISMA-aligned systematic review and meta-analysis. Every claim traced to a verbatim source quote. Structured data you can build a thesis on — delivered in days, not months.

Free scoping assessment What you get

The problem with literature reviews

You already know the evidence needs to be synthesised properly. But between teaching, fieldwork, and writing, there are never enough hours to screen thousands of papers, extract data systematically, and trace every claim back to its source. Supervisors expect PRISMA-level rigour. Summarisation tools fabricate citations. And manual extraction takes months of work that delays your entire timeline.

The time problem

A single systematic review takes an average of 67 weeks. Your thesis timeline does not have 67 weeks to spare on one chapter.

The rigour problem

Supervisors and examiners can tell the difference between a proper structured review and a narrative summary. ChatGPT output will not survive a viva.

The scale problem

Your search returns 2,000 papers. You need to screen, extract, and synthesise them systematically — with an audit trail showing how you got from corpus to conclusions.

What you get

Every tier includes structured data extraction, source-verified quotes, and a full audit trail.

Literature Review Starter

The entry point for most PhD students

2–3 days

Mini systematic review covering approximately 30 relevant papers. Structured data extraction across methodology, findings, and quality. Short synthesis report with cited claims. Enough to draft a thesis chapter or assess whether a full analysis is worth commissioning.

Structured extraction · Source-verified quotes · CSV data export · Short synthesis report
Landscape Scan

Full corpus discovery across 10+ academic databases. Thematic overview of the evidence base, methodology landscape, and quality distribution. Identifies gaps and clusters in the literature. Ideal for scoping a thesis topic or framing a grant application.

3–5 days
Deep Analysis

Full pipeline analysis. Credibility scoring, claim grouping, cross-validation, quantitative meta-analysis with forest plots, and a publication-ready report. For thesis chapters that need to demonstrate command of the field, or for papers targeting peer-reviewed journals.

5–7 days

How it works

1
You send the question. Your research question, field, and what you need the output for (thesis chapter, grant, paper).
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2
I search 10+ databases. Systematic corpus discovery, screening, full-text extraction, and structured data analysis.
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3
You get structured results. HTML report with interactive citations, CSV data export, and full bibliography. Every claim cited.

Starter reviews delivered in 2–3 days. Full deep analysis in 5–7 days.

Not summarisation — structured evidence synthesis

Summarisation tools generate plausible-sounding text from training data. This is structured evidence extraction from real papers, with a verifiable audit trail at every step.

Dimension ChatGPT / Perplexity Evidensity
Source material Training data (static, undated) Live academic databases
Citations Frequently fabricated Real papers, verified quotes
Methodology Unstructured prompt-response PRISMA-aligned pipeline
Data extraction Narrative summary Structured fields, CSV export
Audit trail None Full provenance at every stage
Quantitative synthesis Not possible Real meta-analysis, forest plots
Supervisor acceptance Unlikely Methodology your examiner will recognise

Questions

Is this legitimate for academic use?
Yes. This is structured evidence synthesis — the same methodology used in published systematic reviews. You receive the full audit trail: search strategy, screening decisions, extraction data, and source-verified quotes. Every claim can be checked against its original paper.
Can I use this in my thesis?
The output is a structured evidence base, not ghostwritten text. You receive extracted data, verified source quotes, and structured findings. You use these to write your own chapters — with confidence that the underlying evidence is real, correctly cited, and systematically gathered.
How is this different from using ChatGPT?
ChatGPT summarises from training data and frequently fabricates citations. This service searches real academic databases, extracts from actual papers, and traces every claim to a verbatim quote with section location. The methodology is auditable and PRISMA-aligned — the kind of structured review process your supervisor expects.
What databases do you search?
Semantic Scholar, PubMed, CrossRef, OpenAlex, arXiv, Europe PMC, CORE, DOAJ, ERIC, and additional sources depending on your field. The search strategy is configured to your specific research question and domain.
How fast is turnaround?
Literature Review Starter: 2–3 days. Landscape Scan: 3–5 days. Deep Analysis: 5–7 days. Turnaround depends on corpus size and the depth of analysis required. Urgent requests can be accommodated — ask when you get in touch.
What format do I receive?
A self-contained HTML report with interactive citation tooltips and verified source quotes. Structured CSV data export for your own statistical analysis or import into Excel / SPSS / R. Complete bibliography in BibTeX and RIS formats for direct import into Zotero, Mendeley, or EndNote.
Can I ask follow-up questions on the same evidence base?
Yes. Once the corpus is built, you can submit new research questions and receive fresh analysis in minutes. This is ideal for PhD students who need different framings for different thesis chapters — the evidence base is already extracted, so each follow-up question is a fraction of the cost.

Free scoping assessment

Send your research question. I will map the evidence landscape — how many papers exist, the major themes, and what a structured review would reveal — and send it back within 24 hours. No cost, no commitment.

Send your research question

or email directly: evidensity.research@gmail.com

† Evidensity Research · Every claim, cited · evidensity.research@gmail.com