AIWIZN

AIWIZN · The Wisdom Engine

The Wisdom of Expert Nurses,Captured. Scaled. Deployed.

AIWIZN is an AI-driven nursing education and competency mastery platform that augments traditional onboarding with immersive, scenario-driven learning — targeting clinical errors, turnover, and time-to-competency across a nurse's entire career lifecycle.

≈ $60K
Cost each first-year RN turnover avoids (NSI 2026)
6–12 mo
Time to independent competency, traditional path (Benner; AACN nurse residency)
$917B
Projected U.S. healthcare workforce shortage cost by 2030 (Mercer / NCSBN / HRSA)

Most single-session onboarding is lost within months — the failure mode AIWIZN is built to fix. (Forgetting-curve literature; Schmidt & Bjork, 1992.)

Sources — NSI Vizient 2026 National Health Care Retention & RN Staffing Report (2025 data, first-year RN turnover ≈ $60,090); Benner (1984) From Novice to Expert; AACN Nurse Residency Program; Mercer US Healthcare Labor Market Report, NCSBN National Nursing Workforce Survey, HRSA projections (2030 figure).

The Problem

Healthcare's most expensive unsolved problem.

First-year RN turnover exceeds 30% nationally (NSI Vizient 2026) — yet most hospitals still rely on slide decks, shadowing, and annual compliance modules for the highest-risk onboarding period. The nursing workforce crisis is not a supply problem.

It is a retention and competency development problem — and no platform has meaningfully addressed it with the rigor the profession demands.

≈ 9.6%
National RN vacancy rate (NSI Vizient 2026)
≈ $60K
Replacement cost per first-year RN turnover (NSI 2026 — ≈ $60,090)
> 30%
First-year RN turnover, national average (NSI 2026)
1:1
Best-practice preceptor ratio — ratios often exceed it on understaffed units

Source — NSI Vizient 2026 National Health Care Retention & RN Staffing Report (2025 data; first-year RN turnover > 30%; per-turnover cost ≈ $60,090). Overall RN turnover ≈ 17%; first-year is the load-bearing figure for onboarding ROI.

The Solution

A virtuous learning flywheel — four stages.

Every design decision is evidence-anchored. Each stage feeds the next and the next refines the first.

  1. Stage 01 · Learn

    SOP → Scenario.

    Clinical policies transformed into rich, animated scenario introductions. No slide decks. Narrative-first, evidence-grounded.

    SOP → Scenario

  2. Stage 02 · Practice

    Simulate & Fail Safely.

    Dynamic patient state machine. Goldilocks difficulty calibration. Fail-forward mechanics — the patient deteriorates on wrong choices. Rescue required.

    Simulate & Fail Safely

  3. Stage 03 · Assess

    Stealth Intelligence.

    No explicit testing. Competency inferred invisibly from every simulation action via Bayesian knowledge networks — a leading approach in psychometric science (Shute & Ventura 2013, Stealth Assessment).

    Stealth Intelligence

  4. Stage 04 · Relearn

    Reinforce & Advance.

    Instant formative feedback. Spaced repetition scheduling. Expert nurse performance back-harvested to seed better scenarios. The system gets smarter with every nurse it trains.

    Reinforce & Advance

The Platform

Ten specialized agents. One coherent learning system.

Each agent owns a distinct stage of the competency lifecycle — policy authoring, narrative generation, simulation, stealth assessment, formative coaching, and lifecycle orchestration.

LearnSOP → Competency

PRAXIS

Transforms clinical policies and standard operating procedures into structured competency maps that downstream agents can build against.

LearnStoryboard Generation

NARRATIVE

Generates rich, evidence-grounded scenario introductions — narrative-first, not a slide deck.

LearnProcedural Animation

VISIO

Renders animated clinical procedures and patient states so learners see — not just read — the situation they are walking into.

PracticeClinical Simulation

SIMULUS

Dynamic patient state machine. Goldilocks difficulty calibration. Fail-forward mechanics — the patient deteriorates on wrong choices and rescue is required.

PracticeAdaptive Difficulty

GOLDILOCKS

Tunes scenario complexity to the learner's current proficiency band — not too easy, not impossibly hard.

AssessStealth Assessment

COGNITA

No explicit testing. Competency is inferred invisibly from every simulation action via Bayesian knowledge networks — the gold standard in psychometric science.

AssessPsychometric Profile

PERSONA

Synthesises a Benner-stage proficiency profile after each session — Novice, Advanced Beginner, Competent, Proficient, Expert.

AssessAnalytics Dashboard

LUMINA

Real-time competency analytics for unit leaders, educators, and chief nursing officers.

RelearnFormative Feedback

RESONANCE

Instant, evidence-anchored coaching that targets the specific gaps detected in the previous scene.

RelearnLifecycle Orchestrator

CONTINUUM

Spaces, sequences, and back-harvests expert performance to seed better scenarios — the system gets smarter with every nurse it trains.

Research Foundation · 21 Years

Twenty-one years of immersive simulation work — now turned on nursing.

ATEN Inc., est. 2005.

AIWIZN evolves from ATEN Inc.'s 21-year portfolio of adaptive, scenario-driven training systems — grounded in evidence-anchored pedagogy and serious-game best practices. ATEN's portfolio spans immersive training for financial-services, life-sciences, and industrial enterprises; AIWIZN extends that lineage to nursing.

Bedside clinical scenario — situational and application-based assessment

Clinical · NBME semifinalist (2015)

Bedside clinical scenarios

Cockpit-based flight training simulator with adaptive instruction

Aviation · Adaptive

Cockpit decision training

Stereoscopic VR view of a clinical training environment

Industry · Immersive

Pharma manufacturing VR

Role-playing classroom decision-making scenario

Education · Adaptive

Role-play decision scenarios

Recognition

Recognized by the institutions that set the bar.

  1. 2017
    Named in industry market forecasts
    Serious Game market forecasts (2017–2023)

    Named in syndicated market-research coverage of the serious-game category. Publisher reference held in the AIWIZN data room.

  2. 2015
    Centennial Competition · Semi-Finalist
    National Board of Medical Examiners (NBME)

    Selected from a global field for clinical-assessment innovation.

  3. 2012
    Excellence in Innovation Award
    JP Morgan Chase

    Recognized for excellence in enterprise innovation across a JP Morgan Chase technology programme.

  4. 2011
    Next Generation Learning Challenge · Finalist
    Bill & Melinda Gates Foundation

    Awarded for adaptive, data-driven learning methodology.

  5. 2010
    Digital Media & Learning Competition · Finalist
    MacArthur Foundation

    Recognised for evidence-anchored learning design.

Aten methodology

Show. Make-them-do. Track. Feedback. Adaptive intelligence.

AIWIZN's flywheel is the clinical implementation of Aten's evidence-anchored adaptive learning loop — the same Cerebrum / Cerebellum / Arete architecture that powered enterprise simulations for large enterprises and was recognized with a JP Morgan Chase Excellence in Innovation Award. Built on serious-game best practices; finalist / semi-finalist in NBME (2015 Centennial), MacArthur (2010 DML), and Gates (2011 NGLC) programs.

Aten adaptive learning methodology cycle

Endorsements

What clinicians say after their first scenario.

Unfiltered first impressions from physicians, radiologists, and nurses who've seen AIWIZN in action.

  1. This is impressive; it needs serious judgement skills!

    Dr. Graham E. Snyder· MD, FACEP

    Advisor · Board-certified emergency physician·Associate Program Director, UNC Emergency Medicine

    Raleigh–Durham, NC

  2. Wow! This is exactly what AI needs to do!

    Dr. Bimal Kumar Parameswaran

    Radiologist·Capital Radiology

    Greater Melbourne, Australia

  3. Amazing — I loved this simulation. This is how I would love to learn!

    Lynn Kenyon· BSN, RN

    Critical Care & Perioperative Nurse·Duke University Health

    Durham, NC

  4. The information was very well explained — a ton of great education for anyone not familiar with these emergencies. It helped me think through prioritization and critical moves.

    Rachel Quade· RN

    Registered Nurse·Duke Regional Hospital

    Durham, NC

Leadership & Advisors

Building the future of workforce intelligence.

Credentialed expertise across clinical, academic, and financial domains.

Founder & CEO · AIWIZN / Aten Inc.

Thomas K Vaidhyan

Architect of the AIWIZN multi-agentic learning platform and founder of Aten Inc. Serial ed-tech entrepreneur across immersive learning, serious games, and AI-driven training simulations, with research partnerships at NC State, Virginia Tech, and Duke. Founding board member of BEST NC and Research Triangle High School. Leads platform strategy, product vision, and investor relations across the 14-month build roadmap.

LinkedIn

Deputy Executive Director, Tennessee Population Health Consortium·University of Tennessee School of Health Sciences — School of Medicine

Annie Baby· MA, MBA, MSN, FNP-BC

Valid active RN and Advanced Nurse Practitioner licensure. Experienced clinical, operational, and business leader across health-system organizations. Pairs frontline nursing practice with health-economics, analytics, and value-based-care strategy — informing how AIWIZN translates nursing-education frameworks into scalable clinical learning architectures.

LinkedIn

Advisor · Board-certified emergency physician·Associate Program Director, UNC Emergency Medicine

Dr. Graham Snyder· MD, FACEP

Board-certified emergency physician (FACEP). Associate Program Director, UNC Emergency Medicine. Engineer-turned-emergency-physician with a long record of clinical champion work on simulation-based training. Advises AIWIZN on SIMULUS physiological fidelity and COGNITA clinical validity.

LinkedIn

Managing Director · Head of Digital Health·EisnerAmper LLC

Arvind Kumar

Healthcare-technology strategist with 25+ years across executive and advisory roles — former CIO at Cincinnati Children's, SVP at Xerox Healthcare, and digital-risk leadership at a Big 4 firm. Adjunct faculty at Harvard School of Public Health, Northeastern, and Suffolk. Advises AIWIZN on responsible AI deployment, clinical validation, and healthcare-technology risk.

LinkedIn

Surgeon · Division Chief, Minimally Invasive Gynecologic Surgery · Co-Executive Director, FastTraCS·University of North Carolina

Dr. Erin T. Carey· MD, MSCR

UNC surgeon-innovator leading the Division of Minimally Invasive Gynecologic Surgery and co-leading FastTraCS, UNC's clinical-innovation accelerator. Pairs procedural rigor with translational research and device design — informing AIWIZN's PRAXIS and NARRATIVE work on procedural fidelity, clinical-judgment formation, and innovation pathways from bedside insight to validated practice.

LinkedIn

Clinical Advisor · Critical Care & Perioperative Nurse·Duke University Health

Lynn Kenyon· BSN, RN

A Duke nurse with clinical range spanning the Cardiothoracic (CT) ICU, CT Operating Room, Hyperbaric Medicine, and Student Health as an Immunization & Allergy Nurse — from high-acuity critical care to preventive health. That breadth is exactly the real-world variation AIWIZN's scenarios are built to reflect. BSN, University of North Carolina Wilmington (UNCW).

Advisor affiliations shown for identification only.

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