PLATFORM · ENTERPRISE DEPLOYMENT
One platform, configured for your constraints.
Regulated work carries constraints a default configuration doesn't reach. We configure the core platform around your requirements—wired to your own information sources, and adapted to the geographies and workflows you actually operate in.
HOW WE CONFIGURE
What configuration covers.
You don't get bespoke software built from scratch. You get the same platform we run for every customer, configured to fit—so you inherit a proven, audit-ready foundation and stay on the upgrade path.
Configuration, not a rebuild
Every deployment is configuration on the same codebase—swappable domain data, config-driven interfaces, and documented integrations—so you adapt the platform rather than rebuild it.
Workflows shaped to your team
Workflows and interfaces are configured around how your team actually works, so the platform fits your process instead of forcing a new one on you.
Your data, your perimeter
Your data is isolated to your organization, hosted where you need it, and encrypted in transit and at rest, with SOC 2-ready access controls baked in.
Your information sources
Wire in proprietary, licensed, or internal data sources beyond the public record, so the platform reasons over the full picture that is specific to you.
Your geographies
Adapt to the regulatory regimes, languages, and market realities of the regions you operate in—not just the US FDA default.
Compliance-by-design
Every configuration is engineered traceability-first, aligned to FDA design-traceability expectations, IEC 62304 configuration management, and SOC 2 Type II controls—so configuration never means unauditable.
A proven core, tailored to you
We bridge the gap between rigorous regulatory requirements and the need for product velocity. Rather than starting from a blank page, we adapt the same core platform we run to your specific context—so your software is compliant today and stays on a maintained foundation as the landscape shifts.Scoped to your constraints
Configuration starts from your domain, your data, and your regulatory context: how the rules apply to your product determines how the platform is set up.
Adaptable, audit-ready software
Because every deployment extends a proven core rather than starting from zero, rapid changes never compromise system integrity or the audit trail. You stay on the upgrade path while the platform adapts to your requirements.
One product, many domains
Domain data, regulatory regimes, and integrations are configuration surfaces on the core platform rather than forks of it, so what one deployment needs strengthens the product every customer runs.
Engineering you can rely on
Integrating digital technology into medical devices takes deep technical rigor. The platform is built to be reliable, compliant, and high-performing, and we run it for you.Data pipelines
The platform ingests and normalizes regulatory, reimbursement, and evidence data on a maintained pipeline—the same one behind every deployment.
Traceable engineering
Every line of code links to a requirement and a risk analysis. We automate the generation of your trace matrix.
HIPAA-ready infrastructure
The platform runs on secure, scalable infrastructure with SOC 2-ready access controls and encryption standards baked in.
IN THE FIELD
Three deployments, three constraints.
What a deployment looks like in practice. Each of these started somewhere the off-the-shelf answer didn't reach—a grant clock, a hardware prototype, a decade of research infrastructure held together by hand. Client details are withheld under confidentiality.
Grant clock · no pathway
Wearable biosensing program
A university program with novel sensing technology, two years of funding, and no regulatory pathway. We sequenced clearance ahead of business model—because the pathway determines what evidence the science has to generate, and evidence produced in the wrong shape cannot be regenerated once the grant is spent.
Working hardware · no ML
Non-invasive biosensing device
Sensor hardware worked; nothing existed between raw output and a trained model. We built the training pipeline—ingestion, time aggregation, feature engineering, cross-validated comparison—then used it to establish that the binding constraint was data collection, not method.
The pipeline is what made the constraint knowable, and it outlives the finding.
Strong models · fragile ground
Clinical AI research program
Peer-reviewed models trained by hand-run scripts scattered across personal machines. We containerized the legacy tooling under an immutability guarantee, so validated analyses stayed valid—which did more to earn the researchers' confidence than any capability we added.
Every result now traces to the code and configuration that produced it.
CHECKABLE WORK
Some of the foundation is public. Go read it.
FDA's eSTAR template is a PDF form, and PDF forms in government use still run on XFA—a format most libraries gave up on. Handling it correctly is not incidental to submissions work; it is the floor. So we wrote the library, and we published it.
Open source · MIT licensed
pdfer
Pure Go, zero CGO, zero external dependencies →
The claims we make about submissions rest on this. You don't have to take our word for how it works.
Read the source on GitHubHave a constraint the standard configuration doesn't cover?
Tell us your environment and requirements—we'll show you how we'd deploy.