The AI-powered platform that transforms unstructured research papers into structured, verifiable datasets. Evidence-linked extraction with human verification — ready for meta-analysis in minutes, not months.
Yet most researchers spend weeks on what SCIDEX does in minutes.
Reading hundreds of papers, copying values into spreadsheets. One study takes weeks. A full review? Months.
When data comes from 50+ papers, checking every value against source text becomes impractical.
Every researcher formats data differently. Merging, standardising, and reconciling is error-prone hand work.
SCIDEX solves all three. AI extraction, evidence-linked verification, standardised export — in one platform.
From paper ingestion to verified data export — a seamless pipeline.
Extract data into configurable tables with evidence-linked citations. Every value traces back to the exact source text and page.
AI proposes, researchers validate. Review, edit, approve, or flag conflicts — with a complete audit trail for every cell.
Automatic inconsistency detection across papers. Flag statistical outliers before they affect your analysis.
Design reusable extraction schemas with custom fields, data types, and validation rules. Share across projects.
Chat with your data conversationally. Ask questions, generate insights, and refine extractions — no query language needed.
Export to CSV, XLSX, or JSON with full provenance metadata. Ready for import into statistical analysis tools.
From paper discovery to export-ready datasets — no training required.
Find papers from PubMed, arXiv, Semantic Scholar, and OpenAlex. Add them to your project with a single click — PDFs download automatically.
LLM-powered parsing reads each PDF, identifies sections, and extracts values into your template's fields. Every extraction cites the source sentence.
Review each extracted value alongside its evidence. Edit, verify, or flag conflicts. The audit trail captures every change.
Export clean, standardised datasets to CSV, XLSX, or JSON. Full provenance data included — ready for SPSS, R, Stata, or Python.
Built by researchers, for researchers. Every feature serves the systematic review methodology — not generic project management.
Every extracted value traces back to its source text with page, section, and paragraph references. Not black-box AI — auditable extraction.
Export clean, standardised datasets with full provenance metadata. Your supervisor, statistician, and co-authors will thank you.
"SCIDEX cut our data extraction time from three weeks to two days. The evidence-linking feature alone saved us from countless back-and-forth verification rounds."
"The conflict detection flagged inconsistencies our manual review missed. We caught three data entry errors that would have affected our meta-analysis results."
"We've used SCIDEX for three systematic reviews now. The template system means each review gets easier as we build on previous extraction schemas."
Start free. Scale when you need more.
For individual researchers getting started.
For active research teams and labs.
For institutions and large-scale reviews.
SCIDEX supports PDF files from any academic source. Our AI parser works with research articles, reviews, conference papers, preprints, and book chapters. Papers can be uploaded manually or imported directly from PubMed, arXiv, Semantic Scholar, and OpenAlex.
Our extraction engine achieves 98% accuracy across standard systematic review fields. Accuracy varies by field type — structured data (numbers, dates, statistics) typically extracts more reliably than free-text descriptions. Every extraction includes a confidence score, and all values are human-verifiable with source-text evidence.
Yes. SCIDEX includes a flexible template system where you define exactly what data to extract: field names, data types, validation rules, and descriptions. Create templates from scratch or duplicate and modify existing ones.
Every extracted value is linked to its exact source text in the PDF — including page number, section heading, and paragraph position. When you review a value, you can open the evidence panel to see the original text and verify accuracy yourself.
SCIDEX exports to CSV, XLSX (Excel), and JSON. All exports include extracted values, metadata (paper title, authors, DOI), and provenance information linking each value to its source. Ready for import into SPSS, R, Stata, Python pandas, or any analysis tool.
Yes. SCIDEX supports multi-researcher collaboration with role-based access. Assign extractions to team members, track verification progress, and maintain a complete audit trail of who changed what.
Yes. All data is encrypted in transit (TLS 1.3) and at rest. PDFs are stored in Cloudflare R2 with zero egress fees. Authentication is handled through Supabase with JWT tokens. We do not train AI models on your extraction data.
Our LLM-based extraction engine supports multiple languages. While English achieves the highest accuracy, the system can extract from papers in other major academic languages. Contact us for specific language support needs.
No credit card required. No configuration needed. Sign up and start your first extraction immediately.