Product Engineering
End-to-end product builds — from the first data model to a deployed production application your team can actually run — for scientific software that a generic dev shop was never built to handle.
TYPICAL CLIENT
A founder or product lead building their first real scientific product
Usually a founder, CTO or product lead at a biotech or diagnostics startup who needs a full product built, not a single feature, and needs an engineering partner who understands samples, assays and study data from day one.
Six concrete deliverables, not a slide deck.
This is exactly what transfers to you at the end of this engagement.
Product requirements & data model documentation
A documented data model that matches your actual samples, assays and study structure, agreed before any code is written.
Fully deployed production application
A live application on infrastructure you control, not a demo environment that needs to be rebuilt to ship.
Admin & user role configuration
Role-based access configured to match how your team and customers are actually organized.
API documentation
Documented endpoints for every integration point, so the product can be extended later without reverse-engineering it.
CI/CD pipeline
Automated testing and deployment, so the next release ships safely without manual steps.
Source code & infrastructure-as-code
Full repository access plus Terraform/CloudFormation configs, transferred outright.
What this service includes
Product discovery & scoping
Requirements and data model defined against your actual workflow before a single screen is designed.
Full-stack application development
Frontend, backend and database built together as one coherent product, not stitched from disconnected pieces.
Scientific data modeling
Samples, assays, batches and provenance modeled correctly from the start, so reporting and analysis hold up later.
Deployment & infrastructure setup
Cloud infrastructure and CI/CD configured so the product ships to production, not just to a staging demo.
What this looks like in a real engagement
Three concrete examples of the kind of work this service covers.
MVP build for a diagnostics startup’s first customer
A first production-ready version of a diagnostics platform, built to onboard a real paying customer, not just to demo well.
Rebuilding a spreadsheet workflow into a real product
A multi-user product replacing a spreadsheet that had quietly become the operational backbone of a growing lab.
Greenfield build ahead of a funding round
A working product built on a tight timeline so a founder had something real to show investors, not mockups.
Why scientific products need the data model right the first time.
Generic product studios are built for SaaS CRUD apps, where the data model is an afterthought that gets refactored later. Scientific products don’t forgive that: samples, batches, assay runs and provenance need to be modeled correctly before any UI gets built on top.
We start every product engagement with the data model, not the screens, so the product doesn’t need a rebuild six months in when reality doesn’t fit the shortcuts that were taken early.
How an engagement runs
Four stages, from initial scope to delivery.
Discover & scope
We map your actual workflow and data before any screens or architecture are proposed.
Design the data model
A data model is agreed that matches your real samples, assays and study structure.
Build & iterate
The product is built in shippable increments, with your team reviewing along the way, not just at the end.
Deploy & support
The application ships to production infrastructure with CI/CD and a plan for ongoing support.
What we build it with
They understood our sample and batch structure faster than engineers we’d hired full-time.
Before you reach out
Both. Many engagements start as a scoped MVP and grow from there, but every build ships to real production infrastructure from day one, not a throwaway demo.
You do, outright. Full source code, infrastructure configs and documentation transfer to you at the end of the engagement.
Yes. We regularly work alongside an in-house team, either leading a specific module or embedding into existing sprints.
Explore related work
Internal Tools & Dashboards
The internal-facing counterpart once a customer-facing product is live.
View APIAPI & Integration Development
Connecting the product to instruments, LIMS or partner systems.
View WEBScientific Web Applications overview
See how product engineering fits into the full service.
ViewBuilding a product and not sure where to start?
Tell us what you’re building and what your data looks like today — we’ll tell you honestly what it takes to ship it.