Trusted by Research Institutions

Automate reproducible
retrospective research

From dataset to STROBE-ready Methods & Results in minutes. AI-assisted write-up, algorithmic analyses, and biostatistician review workflows.

HIPAA Compliant
SOC 2 Certification in progress
De-identified by default
Automated Workflow
Upload Dataset
Define Cohort
Select Variables
Choose Analyses
Run Analysis
Export Results
Publication-Ready Output
Demographics Baseline Characteristics
Statistics Regression & Analysis
Manuscript Methods & Results
0x
Faster Analysis
Months to minutes
0%
Reproducibility
Audit-ready outputs
0+
Databases
Supported
0%
Compliance
HIPAA-aligned

Supercharge your research

Our platform automates every step of the research workflow, allowing your team to focus on interpretation and clinical insights.

Multi-table dataset integration

Automatically detect relationships between CSV files, identify join keys, and combine multiple tables seamlessly. Supports complex multi-table datasets with automatic schema detection.

Real-time cohort preview

Define inclusion and exclusion criteria with instant sample size updates. See your cohort size change in real-time as you refine your filters, ensuring optimal study design.

Intelligent variable detection

Automatic variable type detection (continuous, categorical, binary). Smart suggestions for outcomes, covariates, and stratifiers based on your research question.

Automated statistical analyses

Run descriptive statistics, logistic regression, linear regression, Cox models, propensity score matching, and more. All analyses run automatically with proper model diagnostics.

AI-powered paper drafting

Generate complete manuscript drafts with abstract, introduction, methods, results, discussion, and conclusion. Includes literature search integration and automatic citation formatting.

Integrated literature search

Search PubMed and Semantic Scholar directly from the platform. Select relevant papers to automatically include in your manuscript references with proper formatting.

How It Works

Not a platform or a tool—complete workflow automation

1

Setup & Dataset Upload

Upload single or multi-table CSV files. Our system automatically detects relationships, identifies join keys, and validates your data structure.

2

Automated Cohort Definition

Define inclusion and exclusion criteria with real-time sample size preview. The system validates your expressions and shows cohort size instantly.

3

Intelligent Variable Selection

Select outcomes, covariates, and stratifiers. The platform automatically detects variable types and suggests appropriate analyses.

4

Automated Analysis Execution

Run descriptive statistics, regression models, and advanced analyses. All models include proper diagnostics, reference categories, and statistical tests.

5

Publication-Ready Results

Get formatted tables, figures, and statistical outputs ready for publication. Export as DOCX, LaTeX, or CSV with proper formatting.

6

AI-Assisted Manuscript Generation

Generate complete paper drafts with methods, results, discussion, and literature citations. All integrated with your actual analysis results.

Compatible with major healthcare databases

Seamlessly integrate with the registries and datasets you already use

AAOS Registry Program
ACS NSQIP
ACS TQIP
ACS NTDB
AJRR
ASCO CancerLinQ
BRFSS
Cystic Fibrosis Foundation
DoDTR
eICU
Flatiron Health
FORCE-TJR
Get With The Guidelines
HCUP Family
KID
MarketScan
Medicaid MAX
Medicaid TAF
MEPS
Medicare Claims
AAOS Registry Program
ACS NSQIP
ACS TQIP
ACS NTDB
AJRR
ASCO CancerLinQ
BRFSS
Cystic Fibrosis Foundation
DoDTR
eICU
Flatiron Health
FORCE-TJR
Get With The Guidelines
HCUP Family
KID
MarketScan
Medicaid MAX
Medicaid TAF
MEPS
Medicare Claims
MIMIC-III
MIMIC-IV
NCDB
NCDR
NHANES
NHIS
NIS
NPTR
NRMI
NSCID
Optum Clinformatics
Pediatric NSQIP
PHIS
Premier Healthcare
SEER
SEER-Medicare
Synthea
STS Databases
TQIP
VA Databases
VPS
MIMIC-III
MIMIC-IV
NCDB
NCDR
NHANES
NHIS
NIS
NPTR
NRMI
NSCID
Optum Clinformatics
Pediatric NSQIP
PHIS
Premier Healthcare
SEER
SEER-Medicare
Synthea
STS Databases
TQIP
VA Databases
VPS

Compliance & data governance

De-identified/public data by default. Institutional datasets run within approved environments. Every action is logged and exportable.

HIPAA-aligned architecture
No default PHI storage
IRB/DUA aware
Institution-controlled connectors
Role-based access
Project-scoped secrets
Full provenance
Cohort spec, code, outputs, hashes

Science & Methodology

Clinometrics automates retrospective research through a reproducible, algorithmic framework. Every analysis follows standardized statistical workflows verified for accuracy and reproducibility.

Algorithmic Study Engine

Structured datasets are parsed through validated templates that detect variable types, manage missing data, and apply regression or matching automatically.

AI Research Assistant

The integrated AI assistant guides study design, cohort definition, and model selection while maintaining transparency and reproducibility in every analytical decision.

Biostatistician Collaboration

Clinometrics connects users with credentialed biostatisticians who verify outputs, review model assumptions, and produce reproducibility reports ready for publication.

Supported Analysis Types

Descriptive Analyses

Summarize populations using frequencies, proportions, and measures of central tendency with automatic normality testing.

Logistic Regression

Binary outcome models with odds ratios, confidence intervals, and model diagnostics (Hosmer-Lemeshow, ROC curves).

Linear Regression

Continuous outcome models with coefficient estimates, standard errors, and R² statistics.

Propensity Score Matching

Reduce confounding through matching algorithms with balance diagnostics and standardized differences.

Cox Regression

Survival analysis with hazard ratios, Kaplan-Meier curves, and time-to-event modeling.

Change-Point Analysis

Identify temporal inflection points using segmented regression and time-series models.

Pilot programs now open

Department and institutional pilots for 2026. Individual sandbox for trainees on synthetic datasets.