Your Biotech Is Moving Faster Than Your Data.
We Speak Biology
and Python.
Data Science & Engineering
From genomic sequencing to environmental sensors, we take your raw scientific data and build reproducible, production-ready workflows. Scanpy, DESeq2, Cell Ranger, custom pipelines — whatever your data demands.
Production ML Systems
We don't build demos. We build ML pipelines that run in your cloud, scale with your data, and hold up under scrutiny. PyTorch, MLflow, Docker, AWS/GCP — deployed, monitored, and documented.
Enablement & Training
We join your Slack, pair with your engineers, and build your team's capability as we go. When we leave, your team is stronger — not dependent.
Data Readiness Diagnostic
A focused 90-minute assessment of your data landscape. You get a written memo with your current state, top 3 risks, and a prioritized roadmap — whether or not we work together.
- Your data sources, storage, and pipeline architecture
- Bottlenecks that will hurt you in 3-6 months
- Prioritized recommendations with effort estimates
- A clear next step — whether that's us or not
FAQ
What types of projects do you work on?
ML pipeline development, genomic and proteomic data analysis, data infrastructure builds, production model deployment, and team enablement. From a two-week data audit to a six-month embedded engagement building your computational biology stack.
How do engagements typically work?
We start with a Data Readiness Diagnostic — a focused assessment of your current data landscape with a prioritized roadmap. From there, engagements can be project-based sprints or ongoing retainers. The same senior people you meet are the ones doing the work.
Do you actually understand our biology?
Yes. Our team comes from bioengineering, gene therapy, and medical informatics — we've published in these fields. We also work with teams in cleantech, environmental science, and agricultural genomics. The data engineering and ML patterns transfer. We don't need a domain tutorial. We need your data.
We're too early for a full-time data hire. Can you still help?
That's exactly who we work with. We're the data science team you plug in until you're ready to build your own — and we can help you hire when you get there.
How much does a typical engagement cost?
Project-based sprints typically range from $15K to $50K. Ongoing retainers start at $8K per month. We also offer a complimentary Data Readiness Diagnostic so you can understand the scope before committing any budget. Every engagement starts with a clear, fixed-fee proposal — no surprises.
Tell Us What
You're Building.
20-minute intro call. No pitch deck. Just tell us where you are.
Book an Intro Call