Clinical trials cost about $1B each and roughly $1M for every day they run late. They are still run on manual data review: people checking data by hand across spreadsheets and PDFs, hoping nothing was missed.
We automate it. Continuous data cleaning, data that stays analysis-ready, and signals across the whole study so sponsors can make decisions on data they trust.
What that means in practice:
- Reconciling data from many systems that describe the same patient differently
- A rules engine expressive enough that new studies get configured, not coded
- Findings a clinician will act on, which means correct and self-explaining
- Real product surface: this is what people stare at all day
In production with pharma sponsors. Small team, second engineering hire, no legacy to defend.
Stack: Django/Python, React, AWS. SOC 2 Type II.
maybe offtopic, but might be relevant for people considering the company; How is the prospect of entering this market with a investor in the space?
Pharma research is very protective of their data. You likely won't get them to share data to provide a generic plataform, right? So I assume you are building tools they can run on top of their data silos? And even then sales will probably not be easy if the tools belong to a competitor.
agentk2049 · · focus · HN ↗
Clinical trials cost about $1B each and roughly $1M for every day they run late. They are still run on manual data review: people checking data by hand across spreadsheets and PDFs, hoping nothing was missed.
We automate it. Continuous data cleaning, data that stays analysis-ready, and signals across the whole study so sponsors can make decisions on data they trust.
What that means in practice: - Reconciling data from many systems that describe the same patient differently - A rules engine expressive enough that new studies get configured, not coded - Findings a clinician will act on, which means correct and self-explaining - Real product surface: this is what people stare at all day
In production with pharma sponsors. Small team, second engineering hire, no legacy to defend.
Stack: Django/Python, React, AWS. SOC 2 Type II.
Comp: $170-220K + equity.
Email us @ careers+hn@octozi.com
iririririr · · focus · HN ↗
maybe offtopic, but might be relevant for people considering the company; How is the prospect of entering this market with a investor in the space?
Pharma research is very protective of their data. You likely won't get them to share data to provide a generic plataform, right? So I assume you are building tools they can run on top of their data silos? And even then sales will probably not be easy if the tools belong to a competitor.