Helping lab scientists set up and monitor high-volume data pipelines
Overview
Background
As Scispot (YC S21) scaled, enterprise labs increasingly needed automated ways to ingest large volumes of result files into their databases. These labs generated hundreds of files each day and required secure data pipelines that could ingest data directly from external cloud networks, without manual uploads.
Data pipeline setup relied on one-off engineering work for each customer. Although functional, this model required significant engineering effort per lab, making enterprise onboarding expensive and difficult to scale.
Timeline
4 months
Team
1 Product manager
3 Engineers
1 Customer success
Responsibility
Product strategy
User research
Interaction design
Prototyping
User Testing
Cross-functional Workshops
Problem
Pilot customers relied on customer success to set up their database schema, delaying activation and reducing conversion.
Business problems
High engineering effort per customer increased onboarding costs
Limited ability to scale enterprise onboarding with existing resources
User problems
Enterprise labs waited 3–6 weeks to get pipelines set up
No visibility into file ingestion or failure states
Every pipeline issue resulted in a support ticket
Solution
A self-serve platform that allows enterprise labs to configure, monitor, and manage their own data pipelines without engineering dependency.
Impact
We launched the self-serve data pipeline experience in January 2025 and rolled it out broadly in April 2025. The platform significantly reduced onboarding effort while improving activation speed for enterprise customers.
480k
Cost saved for onboarding
35 → 5 hrs
Reduction in time spent by engineers
6 → 2 week
Reduction in time taken for activation