Flux Data Solutions
Portal

Production AI and data infrastructure with healthcare-grade rigor.

Most proofs of concept stall out in a slide deck. We focus entirely on engineering systems for real-world deployment.

Start a conversation // 30-min intro · no slides
01  /  Services

Three things
we do well.

Our team brings wide-ranging engineering capabilities, but we target our consulting where deep technical expertise moves the needle. We are transparent about where we add maximum value and where we don't.

01

Healthcare Data Engineering

Modern lakehouse architecture (Databricks, Fabric, Snowflake) tuned for clinical, laboratory, and EHR data. HIPAA-aware by default. Built to scale past the demo.

Pain Points
  • Your "data" is spreadsheets, SharePoint, mounted drives, and a dozen vendor exports that don't agree. All of it has to become one pipeline you can trust.
  • The modern stack you already built is fighting you: tangled dataflows nobody fully understands, dashboards that crawl or quietly leak data across clients.
  • Databricks
  • Fabric
  • Medallion
  • HIPAA
SOURCES Spreadsheets SharePoint Mounted drives Vendor exports BRONZE raw · as-landed quality gates SILVER validated · conformed GOLD clinical-ready · served SERVED TO BI tools Models Clinicians Clients
Fig. 01 — Medallion architecture: source chaos to clinical-ready.
02

AI & LLM Systems

Custom models, RAG pipelines, evaluation frameworks, and the unglamorous infrastructure that makes them reliable. From pilot to production deployment.

Pain Points
  • A RAG prototype that demos beautifully and falls apart on the first real question, with no eval harness to even measure how often.
  • An LLM rollout across a team with no guardrails on ownership or what's safe to expose, before it becomes a compliance problem.
  • LLMs
  • RAG
  • Evals
  • MLOps
0 20 40 60 80 100 v0.1 v0.2 v0.3 v0.4 v0.5 v0.6 EVAL HARNESS ADDED Release Eval Pass Rate (%) Curated demo set Real user questions · 95% CI
Fig. 02 — You can't fix what you don't measure.
03

ML for Diagnostics & Life Sciences

Predictive models that hold up to regulatory scrutiny and clinical reality. Power analysis, validation cohorts, and honest communication of uncertainty.

Pain Points
  • A clinical model that works in a notebook but no clinician trusts enough to act on.
  • A diagnostic model that has to survive regulatory scrutiny — validation cohorts, honest uncertainty — not just a good AUC.
  • Validation
  • Stats
  • Biomarkers
0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 n=1850 n=680 n=430 n=300 n=250 n=270 n=460 n=820 n=1150 n=2050 Mean Predicted Probability Fraction of Positives Perfectly calibrated Calibrated model · 95% CI
Fig. 03 — Calibration, not just a good AUC.
Also available

Smaller engagements, advisory, and adjacent work.

  • Data strategy & org design

    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.

  • Technical due diligence

    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.

  • Career coaching

    For senior data and AI practitioners moving toward executive roles.

02  /  About
Independent practice

Built by hands
that ship code.

PhD, computational biology
Nearly two decades in
bioinformatics & programming

Widely cited peer-reviewed
publications · production
systems in clinical use

Flux Data Solutions exists because much of what gets called "AI consulting" fails in production. In healthcare, the data is messy, the regulations are real, and the stakes are clinical.

The practice is led by a PhD-trained computational biologist with nearly two decades of bioinformatics and programming experience spanning academic research and industry. This includes peer-reviewed work on clinical genomics tools still widely used today, alongside production AI and data systems deployed inside clinical and diagnostics organizations.

This background brings a specific discipline to client engagements: rigorous statistics, honest evaluation, and infrastructure built to scale past the demo.

While deeply rooted in healthcare and life sciences, this methodology regularly handles complex financial, sales, and operations data. The engineering rigor remains the same wherever the data is messy and the stakes are high.

03  /  Company portal

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Philadelphia skyline and the Schuylkill River from an office window.

04 / Get in touch

Tell me about your data problem.

The best engagements start with a 30-minute conversation. No slides, no pitch, just whether there's a real problem worth solving together.

Book an intro call hello@fluxdatasolutions.com