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Philip Morales
GDTS / DIAS™ · Methodology

The Adoptiv Method™

Users don't build from a blank canvas — they assemble from a governed library of pre-approved agents and agentic flows, with regulatory controls enforced on every one, and the platform guiding them from prompt to production.

The Adoptiv
Loop

assemble · harden · ship · adopt
Build
↓
Industrialize
↓
Deploy
↓
Adopt & Scale
approved parts,
guided assembly,
by default
"Assemble from
approved."

Pre-Approved Agents

A catalog of vetted, versioned agents — users assemble from approved parts instead of building from scratch.

Governed Agentic Flows

Multi-step workflows, pre-approved and ready to configure — adopt a proven flow, not a blank canvas.

Regulatory Controls

HIPAA, SOX, NIST AI RMF & EU AI Act mapped in — compliance agents check every agent and flow before it ships.

Guided Assembly

The platform walks each user from prompt to production — golden paths, in-context help, guardrails that lighten as skill grows.

AI Testing & Evals

Agentic QA, evals & red-team suites form the quality gate every agent and flow must pass.

Compounding Reuse

Every approved agent and flow makes the next build faster, cheaper & safer — the library compounds.

95% of GenAI pilots deliver no measurable P&L impact. 42% of companies abandoned most AI initiatives in 2025 — up from just 17% a year earlier.
The constraint was never the models — it was the missing path. A governed library of pre-approved agents, flows, and controls closes the gap.
Read the white paper — The Adoptiv Method™ · GDTS / DIAS™
Philip Morales · VP, Healthcare AI & Digital Transformation · Digital Intelligence Advisory Services (DIAS™)
Fig. 1 — Adoptiv Method Ecosystem | GDTS / DIAS™ Methodology | V1.1 · July 2026 | Sourced Claims Validated 3/3 · 100%
Sources: MIT NANDA, The GenAI Divide: State of AI in Business (2025) — 95% no measurable P&L impact. S&P Global Market Intelligence / 451 Research, Voice of the Enterprise (2025) — 42% abandoned most AI initiatives, up from 17%. Framework mappings (HIPAA, SOX, NIST AI RMF, EU AI Act) are representative; KPI targets are illustrative planning baselines.
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