Frekil GTM brain

Frekil sells an AI real-world evidence platform to life sciences teams conducting auditable observational studies on clinical data.

category

Real-world evidence generation

market profile

  • text: After drug approval, safety commitments, payer questions and label expansion can require observational studies based on fragmented clinical data.
  • text: Real-world evidence buyers include pharma, biotech, CRO and clinical research teams; scientific rigor and reproducibility are central to adoption.
  • text: Frekil previously launched around medical imaging annotation; current positioning is real-world evidence generation.

personas

  • title: Head of Real-World Evidence or Epidemiology
    pains:
    • Post-approval study requests arrive faster than teams can design, execute and document them
    • Must defend confounding control and trace every result to source data and code
  • title: HEOR and Market Access Director
    pains:
    • Payers and health technology assessment bodies require comparative effectiveness and value evidence
    • Separate data extraction, analysis and reporting slow reimbursement evidence
  • title: Biostatistician or Clinical Researcher
    pains:
    • Complex cohort extraction and sensitivity analyses require substantial programming
    • Black-box outputs cannot be independently validated for a study
  • title: Drug Safety or Pharmacovigilance Lead
    pains:
    • Post-authorization safety commitments and emerging signals require defensible follow-up studies
    • Delayed evidence can slow safety decisions

icp

  • text: Pharma and biotech organizations with approved or late-stage drugs and recurring post-marketing safety, HEOR or label expansion evidence needs.
  • text: CROs and clinical research teams running observational studies using EHR, claims or registry data and requiring documented statistical workflows.
  • text: Organizations able to run evidence generation against their own cloud data environment, including Databricks or Snowflake.

message pillars

  • text: Cover the whole observational study with team oversight.
  • text: Build post-approval evidence for safety and access decisions.
  • text: Make statistical evidence inspectable and reproducible.
  • text: Keep sensitive clinical data in the customer's cloud.

objections

  • objection: Can AI-generated analyses withstand regulatory or scientific scrutiny?
    response: Evaluate a representative study with scientists reviewing the protocol, code, bias assessment and traceability before relying on results.
  • objection: Our clinical data cannot leave our environment.
    response: Discuss the stated VPC deployment and validate the customer's specific security architecture and data access controls.
  • objection: Our data and validated pipelines are too specialized.
    response: Test a limited study on the actual schema and review integration with existing SOPs, code and validated libraries.

competitors

  • name: Aetion
    website: https://www.citybiz.co/article/673576/qa-with-jeremy-rassen-scd-co-founder-and-ceo-of-aetion/
    why: Provides real-world evidence analytics for life sciences and regulators.
  • name: TriNetX
    website: https://www.cbinsights.com/esp/life-sciences/biopharma-tech/real-world-data
    why: Offers a clinical research network and real-world evidence capabilities.
  • name: Flatiron Health
    website: https://knowmorepharma.com/vendors
    why: Provides oncology-focused real-world data and evidence.

influencers

  • name: Shivesh Gupta
    url: https://www.linkedin.com/in/shivesh-gupta-iitb
    why: Frekil co-founder discusses the company's real-world evidence work.

keywords

  • real world evidence generation platform
  • RWE post marketing safety study
  • HEOR evidence automation
  • target trial emulation software
  • real world data cohort extraction
  • pharma observational study software
  • statistical analysis plan automation

voice

  • Scientific and evidence focused
  • Direct about regulatory scrutiny
  • Confident and practical

signals

  • text: A pharmaceutical company has a new post-authorization safety commitment or emerging safety signal requiring observational analysis.
  • text: A biotech is preparing payer or HTA evidence for an approved product or pursuing an indication expansion.
  • text: A research team is hiring epidemiologists and statistical programmers to increase RWE study throughput.

stack

  • Databricks
  • Snowflake

pricing

model: unknown

motion

sales_led

channels

  • LinkedIn
  • search
  • ISPOR events
  • referrals
  • YC

confidence

high

Founders

  • name: Nikhil Tiwari
    title: Founder/CEO
    role: CEO
    bio: Co-founder & CEO at Frekil | IIT Bombay graduate | Prev SWE @ Stripe, Amazon, Marsh&McLennan | Semester Exchange at University of Geneva | Healthcare AI research @ IIT Bombay
  • name: Shivesh Gupta
    title: Founder/CTO
    role: CTO
    bio: I’m the co-founder and CTO at Frekil, building AI-powered workflows to generate automated real world evidence of drug performance. Previously, I worked as a systems software engineer at Sony Japan and declined a full-time offer from an HFT to build Frekil. I graduated from IIT Bombay this year, where I also led the institute web and coding club.

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