Sutrix GTM brain

Sutrix reconciles patient records and applies study rules to create reviewable research datasets for clinical teams.

category

Clinical research data preparation

market profile

  • text: Research teams reconcile EHR extracts, notes, registries and surveys before a study dataset is analysis-ready.
  • text: Hospitals often transfer clinical trial data manually from electronic health records into study systems, creating an automation opportunity.

personas

  • title: Principal investigator or clinical research director
    pains:
    • Publication and analysis depend on months of data cleaning.
    • Changed definitions or inconsistent sources make study results harder to reproduce.
  • title: Clinical data management lead
    pains:
    • Staff reconcile inconsistent codes and missing values across sources.
    • Must explain the evidence, transformation and review history behind each field.
  • title: Research coordinator
    pains:
    • REDCap exports contain coded checkboxes and blanks that require manual chart review.
    • A repeated analysis requires redoing cleanup and resolving conflicting entries.

icp

  • text: Hospital and academic research groups with EHR, REDCap, registry or wearable data and recurring study preparation workloads.
  • text: Clinical research networks and biopharma data teams that must reconcile multi-source patient data and document decisions; size is unspecified.

message pillars

  • text: Accelerate preparation before analysis.
  • text: Keep each value connected to its source evidence.
  • text: Reuse definitions when the data or protocol changes.

objections

  • objection: How can we trust AI-prepared clinical data?
    response: Pilot against a manually reviewed cohort and inspect evidence, reconciliation rules and uncertain cases before relying on the output.
  • objection: Can the system operate under our patient data controls?
    response: Review the actual deployment, access controls and security terms; YC describes deployment inside each team's environment.

competitors

  • name: Yonalink
    why: Connects EHR and clinical study systems to reduce manual data movement, an adjacent study-data workflow.
  • name: Atropos Health
    why: Uses healthcare data to generate research-grade evidence, overlapping with clinical research data work.
  • name: Mendel
    why: Structures and processes clinical data for healthcare and research use cases.

influencers

  • name: Supratik Panuganti
    url: https://www.linkedin.com/posts/supratik-panuganti-4732532a4_im-excited-to-share-that-sutrix-yc-f26-activity-7503574962478215169-NIAj
    why: Co-founder discussing Sutrix and its research workflow.

keywords

  • clinical research data preparation
  • EHR data abstraction
  • REDCap data cleaning
  • clinical data reconciliation
  • study ready datasets
  • real world evidence data preparation

voice

  • Practical
  • Clinically grounded
  • Focused on traceability

signals

  • text: A study is combining EHR extracts with surveys or wearable data and faces a chart review backlog.
  • text: A research organization repeatedly cleans registry exports or revises cohort definitions.

stack

  • REDCap
  • EHR

pricing

model: unknown

motion

sales_led

channels

  • LinkedIn
  • YC directory

confidence

medium

Founders

  • name: Ritvik Panuganti
    title: Founder/CEO
    role: CEO
    bio: B.S. Neuroscience, Georgia Tech. Published clinical researcher at Hospital for Special Surgery, Emory, and Georgia Tech. Built a multi-sport injury surveillance system at HSS now running across 700+ teams and 30+ tournaments. Led a 300-participant IRB-approved concussion study at GT and prepared a VR concussion assessment tool for FDA 510(k) submission.
  • name: Supratik Panuganti
    title: Founder/CTO
    role: CTO
    bio: Previously founded and exited an AI security company backed by a16z Speedrun. Software engineer at Amazon. Georgia Tech CS + Math (dropped out).

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