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Researchers
Turn academic papers into a queryable literature database
Academic papers, study data, and literature reviews generate mountains of unstructured information. Endpoints extracts authors, methodology, key findings, statistics, and citations into structured data so you can query and compare across your entire literature base.
The problem
- Academic papers, study data, and literature reviews generate mountains of unstructured information.
- Keeping track of methodology, findings, and citations across dozens of papers is a nightmare.
- There is no structured way to query across papers.
The solution
- Scan research papers, study reports, and datasets.
- Endpoints extracts authors, methodology, key findings, statistics, and citations into structured data.
- Build a queryable literature database.
How it works
Step 1
Upload your papers
Upload 20 papers from a literature review
Step 2
AI extracts the data
AI extracts: title, authors, journal, methodology, sample size, key findings, p-values
Step 3
Query your endpoint
Query /literature-review/sleep-study for all structured paper data
Step 4
Compare across papers
Compare methodologies and findings across all papers via API
Sample API response
GET/literature-review/sleep-study
{
"title": "Effects of Blue Light on Sleep Quality",
"authors": [
"Dr. Sarah Kim",
"Dr. James Park"
],
"journal": "Journal of Sleep Research",
"year": 2025,
"methodology": "Randomized controlled trial",
"sampleSize": 240,
"keyFindings": [
"Blue light exposure reduced sleep quality by 23%",
"Effect was strongest in 18-25 age group"
],
"statistics": [
{
"metric": "p-value",
"value": 0.003
},
{
"metric": "effect size",
"value": 0.45
}
],
"citations": 47
}Ready to get started?
Turn any document into a structured API endpoint. Free to start, no credit card required.
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