Flux Data Solutions partners with healthcare, diagnostics, and other data-intensive teams to build the systems they actually deploy — not the proofs of concept that die in a slide deck.
Most consulting engagements try to be everything. We're disciplined about a small set of problems where deep technical expertise actually changes the outcome — and honest about what sits outside that.
Custom models, RAG pipelines, evaluation frameworks, and the unglamorous infrastructure that makes them reliable. From pilot to production deployment.
Modern lakehouse architecture — Databricks, Fabric, Snowflake — tuned for clinical, laboratory, and EHR data. HIPAA-aware by default. Built to scale past the demo.
Predictive models that hold up to regulatory scrutiny and clinical reality. Power analysis, validation cohorts, and honest communication of uncertainty.
Smaller engagements, advisory, and adjacent work.
Advisory for CDOs, CTOs, and CMOs standing up data functions.
A CDO or CMO standing up a data function who needs an architecture they won't regret in 18 months.
For investors and acquirers evaluating data and AI assets.
A data or AI asset that needs an honest valuation — whether it's yours to monetize or a target's "AI" to verify before you buy.
For senior data and AI practitioners moving toward executive roles.
Flux Data Solutions exists because most of what gets called "AI consulting" doesn't survive contact with production — especially in healthcare, where the data is messy, the regulations are real, and the stakes are clinical.
The practice is led by a PhD-trained computational biologist with a decade of experience spanning academic research and industry. Peer-reviewed work on bioinformatics tools that are still widely used in clinical genomics. Production AI and data systems currently deployed inside a clinical diagnostics organization.
The discipline that comes from that background — rigorous statistics, honest evaluation, infrastructure built to scale past the demo — is what we bring to client engagements.
We work primarily in healthcare, diagnostics, and life sciences, but the underlying methodology travels well to any industry where the data is messy and the stakes are real. Founder details are shared during intro conversations.
The best fit engagements usually start with a 30-minute conversation — no slides, no pitch, just whether there's a real problem worth solving together.
