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Government health · Data science · Software

The nation’s health, optimized through engineering.

Hale Data Sciences builds data platforms, machine-learning systems, and secure software for the government agencies that safeguard American health.

HDS · Population health

SYNDROMIC · WK 36

Ingest · 24h

12.4M

+2.1% vs prior day

Forecast Δ · 4wk

+8.2%

model CI ± 1.9

Open signals

1

wk 30 · under review

Respiratory ED visits per 100k — observed & 8-week forecast

102030OCTDECFEBAPRJUNFORECASTflagged
ObservedForecast ± CIExpected rangeFlagged
Population health console — illustrative product concept

Supporting missions across

VAHHSCMSCDCDHANIHState & Local

How we deliver · The Dark Factory™

Every release, off a governed production line.

Every release class we ship — software, data, models, AI systems, decision products — moves through its own proprietary Dark Factory pipeline. Specs go in continuously; signed, evidence-backed releases come out. Every stage clears three layers of validation: programmatic checks, AI evaluation, and human sign-off. And the line learns: what the evaluation gates find feeds the next round of specs.

HDS · Dark Factory

RUN 2381 · CHECKS 9/9

Diagram of the Dark Factory delivery pipeline. Specifications of every kind, written by people, arrive continuously and converge on a specification gate at the factory wall — the barrier to entry: no spec enters the line without clearing it. Inside the sealed factory, three verification gates each apply three validation layers: programmatic, ai evaluation, human sign-off. A signed release exits and fans out into the releases this line ships: software, data, models, decisions. Evidence accrues on a ledger at every gate — 1,284 artifacts this run, reviewed by people. A feedback loop returns what the evaluation gates find — failed checks, AI-review findings, human review notes — to the specification gate, sharpening the next round of specs before they enter the line. Fabricated illustrative data.

Every gate, three layersPROGRAMMATICAI EVALUATIONHUMAN SIGN-OFF
Dark Factory run view — illustrative product concept

What we do

Four disciplines. One delivery standard.

Everything we build is engineered for the realities of government health programs: sensitive data, strict accreditation, and zero tolerance for downtime.

Domain depth

Healthcare is where we go deepest.

From FHIR interoperability to claims analytics at CMS scale, our teams work in the grain of health data — its standards, its privacy law, and its clinical stakes. The same engineering travels well to any mission built on sensitive data.

Claims & Payment Integrity

Fraud, waste, and abuse detection across billions of claim lines; risk adjustment; prior-auth decision support.

Population Health & Surveillance

Syndromic surveillance, outbreak detection, and jurisdiction dashboards that hold up during a crisis.

Clinical Operations

Risk stratification, capacity forecasting, clinical NLP, and decision support inside the EHR workflow.

Research Data Platforms

OMOP research enclaves, registry systems, de-identification, and reproducible analysis environments.

How every release is validated

  1. Gate 1 · Programmatic

    Checks run on every artifact

    Tests, static analysis, and policy checks execute continuously — nothing advances with a red result.

  2. Gate 2 · AI evaluation

    Models judge the work

    Automated evaluation reviews each release candidate against its spec before a person ever sees it.

  3. Gate 3 · Human sign-off

    A person signs the release

    Every release ships signed, with its evidence ledger attached — accreditation accrues from the first commit.

Why Hale Data Sciences

Built different, on purpose.

Small-business speed, enterprise rigor

Compact teams with direct access to principals — governed by the same engineering discipline you'd expect from a prime ten times our size.

Compliance is a feature

NIST 800-53 controls, audit trails, and 508 accessibility are designed in from the first sprint, so accreditation never becomes a rewrite.

Founded at the intersection

Hale Data Sciences was founded by a psychiatrist and an AI systems engineer. That pairing runs through every delivery team, so our models reflect medical reality — not just the training data.

Bring us a hard problem.

Whether you’re shaping a requirement or rescuing a program, we’ll show you working software before we show you a slide deck.

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