Case Studies
Real roles, real teams, real outcomes
A few examples of the kinds of teams Silicon Development supports and the work those engineers were responsible for once they were inside the team.
Selected client work
Each case shows the operating context, the role Silicon Development played, and what changed.
Challenge
The company needed engineers who could work inside its product teams across clinical measures, data infrastructure, BI, and platform operations, supporting end customers at healthcare systems in the US, UK, and Middle East. The work demanded domain understanding, regulatory awareness, and the ability to operate inside a complex, multi-team organization through reorganizations, platform migrations, and a Databricks rollout.
Silicon Development's role
Silicon Development provided embedded engineering support across 9 client teams over 6+ years. Engineers reported directly to client engineering managers, participated in the client's own performance review system, and held responsibility for named end-customer accounts.
Key work delivered
- Record number of clinical quality measures certified across HEDIS, CMS, and MIPS
- Reduced Rules Engine out-of-memory errors from several per month to a few per year
- Delivered Readmission and Length of Stay metrics to Databricks production
- Migrated the Order Set Dashboard from Power BI to Tableau, expanding the client's addressable market
- Supported a successful Epic Clinical Implementation production go-live at a major academic medical center
- Grew an engineer from contributor to architect, leading the v2 Measure Results system redesign
Outcome
The engagement has run continuously since 2020 through an acquisition, multiple reorganizations, and corporate restructurings. The client's own performance reviews and leadership feedback consistently describe SD engineers as top contributors.
Team: 14+ engineers over 6+ years across 9 client teams. Average tenure: 3+ years.
Read full case study →Kinds of work these teams needed
The common thread is embedded engineering work in environments where quality and context matter.
Full-stack SaaS platform build
Consumer Tech / Data Platform
Silicon Development was the primary engineering team for a consumer data company, building the full SaaS platform, data ingestion pipeline, and supporting ML models. The team built web and mobile applications from start to finish, working directly alongside the client’s product team.
Rules engine migration
HealthTech / Performance
Migrated a critical rules engine from a monolithic Ruby application to a standalone Java Drools service for a healthcare SaaS platform. Achieved a 19x performance improvement, reducing processing time from 10 hours to under 90 minutes.
AI-powered document redaction
LegalTech / FinTech
Built a file upload processing system that uses AI to automatically redact sensitive information for an enterprise litigation platform. Part of a broader embedded engineering engagement that increased team velocity by over 50%.
Cloud migration and DevOps
BioPharma / Cloud
Migrated a SaaS application from Virtual Machines to a native cloud application service on Microsoft Azure with automated DevOps deployment. Part of a multi-year engineering partnership supporting a scientific computing platform.
Research data visualization
BioPharma / Data
Built a collection of data visualizations for a drug discovery platform to surface research insights for scientific decision-making. Required engineers who could learn domain-specific concepts and collaborate with research scientists.
Acquisition-ready engineering
HealthTech / M&A
Played an integral role in the engineering work that helped a healthcare SaaS platform get acquired by a larger health tech firm. Embedded engineers contributed to feature delivery, code quality, and performance optimization throughout the acquisition process.
What these examples show
The same operating pattern shows up across very different client environments.
Engineers worked inside the client's team and workflow. Across every engagement, Silicon Development engineers used the client's tools, process, and communication rhythm rather than operating as a separate delivery unit.
The work was technically demanding. Rules-engine migrations, cloud platform architecture, AI-assisted document processing, scientific data visualization. These are roles where domain understanding and engineering judgment matter.
Complex environments were normal, not unusual. Healthcare data platforms, litigation systems handling sensitive information, drug discovery tools processing clinical data. Silicon Development's strongest engagements tend to be in environments where quality, security, and domain fit are non-negotiable.
The work produced visible outcomes. 19x performance improvements. 50%+ velocity increases. MVP-to-production platform builds. Acquisition support. Those outcomes came from engineers who were embedded deeply enough to make real contributions.
Good engagements tend to expand. Clients that start with Silicon Development often extend the work or add roles once the model proves itself inside the team.
These examples show what good embedded work actually looks like
Complex environments, real ownership, measurable outcomes. That is where the model is strongest.