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 while supporting downstream healthcare delivery needs. The work demanded domain understanding, regulatory awareness, and the ability to operate inside a complex, multi-team organization through reorganizations, platform migrations, and analytics stack changes.
Silicon Development's role
Silicon Development provided embedded engineering support across multiple client teams over 6+ years. Engineers worked directly with client engineering managers and operated inside the client's existing product, data, and operations workflows.
Key work delivered
- Delivered a large volume of clinical quality measure updates and certifications across HEDIS, CMS, and MIPS reporting frameworks
- Reduced recurring Rules Engine memory failures through profiling and long-term fixes
- Moved key reporting workloads onto a modern data platform
- Migrated a flagship analytics dashboard to a newer BI stack
- Supported a successful enterprise healthcare implementation go-live
- Developed an engineer from contributor to architect over the life of the engagement
Outcome
The engagement has run continuously for more than six years through an acquisition, multiple reorganizations, and corporate restructurings. SD engineers took on long-tenure, high-trust responsibilities across the life of the relationship.
Team: 14+ engineers over 6+ years across multiple 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.