Sutrix
Sutrix deploys AI within hospital research teams’ existing systems to turn fragmented EHR records, clinical notes, wearables, and surveys into study-ready datasets, cutting data preparation time by 80%. The platform runs each study as a governed, repeatable workflow with a complete audit trail, enabling biostatistics cores to process messy, heterogeneous data and deliver reproducible, publishable results in days rather than weeks.
- Data & Analytics
- Healthcare Technology
- Artificial Intelligence
- Software Only
Funding
Raised to date
$500KRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Founder details are not available yet.
Product
Problem
Biostatistics cores receive heterogeneous Excel files from investigators, requiring manual cell checks, custom scripts, and iterative cleaning that consumes roughly a quarter of study time. With only a handful of biostatisticians serving hundreds of investigators, studies queue for weeks, delaying reports and slowing research timelines.
Solution
Sutrix deploys integrated analysis systems that enable biostatistics cores to process large, fragmented, messy datasets and deliver publishable results in days rather than weeks. The platform runs every study as a governed workflow with a complete record of incoming data, cleaning operations, approved plans, executed code, validation steps, and sign-offs, ensuring full reproducibility. It automates consistency checks and standardizes the analysis pipeline, reducing manual effort and tripling study capacity. The system is built for research teams that must demonstrate their work, providing audit-ready documentation for every analysis.
Target Audience
Primary customers are biostatistics cores at academic research centers and clinical research organizations that manage high volumes of investigator-initiated studies and need reproducible, audit-ready analyses.
Features
- Governed workflow with complete audit trail: data provenance, cleaning decisions, approved plans, code execution, validation, and sign-offs
- Automated consistency checks for SAS and R, reducing manual cell-by-cell review
- Handles heterogeneous input formats, including Excel files of different shapes from phase 1/2 trials and chart reviews
- Multi-source clinical data reconciliation across EHR warehouses, registries, and claims extracts
- REDCap and survey export cleanup with automated blank chasing and coded-field resolution
- Registry extract cleaning and comparison that normalizes legacy conventions like 999/888 missing values and changing column meanings
- Methods and results drafting that generates manuscript sections directly from the analysis output, preventing number drift
- SOC 2 compliant with AICPA Trust Services Criteria for security, availability, and confidentiality
- HIPAA compliant with administrative, physical, and technical safeguards for protected health information
- Zero-trust security by design, applying the same identity verification and time-bound permissions to human users and AI agents