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 generationmarket 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 Epidemiologypains:
- 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 Directorpains:
- 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 Researcherpains:
- Complex cohort extraction and sensitivity analyses require substantial programming
- Black-box outputs cannot be independently validated for a study
- title: Drug Safety or Pharmacovigilance Leadpains:
- 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: Aetionwebsite: 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: TriNetXwebsite: https://www.cbinsights.com/esp/life-sciences/biopharma-tech/real-world-datawhy: Offers a clinical research network and real-world evidence capabilities.
- name: Flatiron Healthwebsite: https://knowmorepharma.com/vendorswhy: Provides oncology-focused real-world data and evidence.
influencers
- name: Shivesh Guptaurl: https://www.linkedin.com/in/shivesh-gupta-iitbwhy: 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_ledchannels
- search
- ISPOR events
- referrals
- YC
confidence
highFounders
- name: Nikhil Tiwarititle: Founder/CEOrole: CEObio: 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 Guptatitle: Founder/CTOrole: CTObio: 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.