Consequential Engineering
Contract engineering for software whose failure has clinical, regulatory or mission consequences, organized as two practices: Consequential Data Engineering, for data platforms, device runtimes and legacy migrations that have to behave the same way every time, and Consequential GRC Engineering, for requirements turned into working systems, repeatable practices and defensible evidence. A named engineer is accountable in both.
Consequential Data Engineering
Sovereign pipelines and safety-critical systems
The problem: Clinical analytics, AI workflows and safety-critical edge systems fail silently when the pipelines and runtimes beneath them lack schema enforcement, timing measured on the target hardware and recorded provenance. Teams built for demos leave 21 CFR Part 11, IEC 62304 segregation and real-time behavior as costly afterthoughts.
What we deliver: Client-owned data platforms and deterministic systems, from healthcare data lakes and OMOP pipelines to RTOS embedded controllers and SaMD architectures, where every transformation and state transition is verifiable.
- Healthcare Data LakeMulti-source clinical warehouse in your own cloud account
- Clinical Evidence & RWE PipelinesOMOP and FHIR data with recorded provenance
- Deterministic AI & Agent GuardrailsSchema-checked inputs and outputs for AI agents
- Operational Truth™ TelemetryOperational evidence stored where you can query it
- Edge & Embedded Systems EngineeringExplicit state machines and latency measured on the target board
- Medical Device & SaMD ArchitectureIEC 62304 segregation, ISO 14971 traceability and a CycloneDX SBOM
- Regulated Platform ModernizationOne capability at a time, with shadow runs and rehearsed rollback
Consequential GRC Engineering
Executable assurance and continuous evidence
The problem: Audit preparation remains trapped in recurring screenshot fire drills and fragile manual spreadsheets, yielding static compliance claims that decay the minute an auditor departs.
What we deliver: We replace manual compliance scrambles with scripted local evidence collectors, control crosswalks in SQL, Git-native test matrices and verification by qualified engineers.
- Automated Evidence MeshQueryable local SQLite evidence store
- Unified Control CrosswalksSOC 2, HIPAA and ISO 27001 controls mapped in SQL
- Continuous Compliance as a ServiceLocal collectors and review by named analysts
- Test Management as CodeCarries the Regulated Software Quality & V&V Engineering service line: V&V plans, protocols and executed evidence in Git, the difference between “we tested it” and a package a reviewer can follow from requirement to result
- Threat Exposure Management & RetestingAuthorized testing and a retest of every remediated finding
- QMSR & ISO 13485 HarmonizationDesign and development file traceability
Healthcare data lake engineering
HL7 v2, FHIR R4 and C-CDA pipelines built in your own AWS or Azure tenant, encrypted with your keys and defined in Terraform that lives in your repository, with a documented exit path.
Ready to Build?
Start with the practice closest to your problem, or talk to an engineer about where your project sits across the two.