AI & Data Systems Portfolio Dossier

Owen H. Eskew, MBA, MSAI

Enterprise architect and AI builder. Twenty-five years across USAF operations, DoD enterprise architecture, and a working AI product studio, with production systems, paying customers, published research, and a published book as verification.

New Braunfels, TX owen.eskew@onsq.net +1 (830) 302-3330, answered by his own AI receptionist onsq.net LinkedIn Active Top Secret clearance Download PDF All capability statements

Contents: At a glance · Live proof · Experience · Portfolio · Technology · Role fit · Research & writing

At a glance

The record in numbers

10+AI systems designed, built, and operated; four in production with real users
25 yrsin IT and data systems, from USAF operations through DoD enterprise architecture to founder
200+DoDAF-compliant architecture artifacts delivered in DoD environments
755KAirmen served by the USAF learning systems he architected
6LLM platforms in shipped work: Anthropic, OpenAI, Google, xAI, Microsoft Copilot, and custom endpoints
10+certifications, including Microsoft Certified: AI Transformation Leader, CompTIA Security+ ce, Azure AZ-900, ITIL, GitLab, Google PM, and DoDAF/TOGAF
3books published, six authored AI curricula, and an ACM SIGCSE 2026 submission
TSActive Top Secret clearance; 25 years in Department of Defense environments

"Advice is easy to sell and hard to verify. So here is the verification: AI products designed, built, and operated, with paying customers, live clients, students, and readers using them today."

Live proof

Verify before you interview

Every major claim in this dossier has a public artifact. Call the phone number above and an AI system he built answers. The rest:

ArtifactWhat it proves
ailura.netAilura AI Receptionist, a production voice/SMS/chat agent platform with paying customers
getailura.comAilura Home Services, a multi-tenant field-service SaaS running a live HVAC company
cheqer.vercel.appCheqer, an AI Bible word-study app: hybrid RAG with published retrieval-quality metrics
onsq.net/portfolioFull product portfolio with the status of each system
onsq.net/capabilitiesCapability statements: commercial, federal, education, speaking
Amazon author pagePublished books, including Image in the Machine (2026)
store.onsq.netONSQ Enterprise Press, a working publishing and e-commerce operation
Experience

Professional experience

Feb – Sep 2026

ServiceNow Business Process Analyst, AFLCMC/HNCD, U.S. Air Force

Centurion (Leidos program). Cyber defense capability delivery on ServiceNow.

  • ServiceNow ITAM, HAM, and SAM for an active acquisition directorate: asset tracking, hardware and software accountability, lifecycle reporting, and CMDB.
  • Authored the directorate's ServiceNow user guide (Zurich release) covering ITSM, HAM, SAM, CMDB, SPM, and Change Management; built UAT test plans and requirements backlogs.
  • Translated operational cyber needs into scoped, testable workflow and integration designs under accreditation and contract constraints.
Mar – Oct 2025

Platform Engineer, Army Software Factory

Strategic Intelligence Inc. (Akima), Austin, TX.

  • Multi-cloud architectures integrating AWS GovCloud, Azure AI Foundry, and Palantir Foundry for enterprise data and AI workflows, plus AI automation frameworks and custom LLM work.
  • CI/CD with GitLab, Terraform, and Kubernetes; coached Army soldier-engineers on cloud platforms, observability, and DevSecOps.
Oct 2023 – Feb 2025

Site Lead and Enterprise Learning Architect, HQ AETC A3G

Strategic Technology Institute, Randolph AFB, TX. Enterprise Architect for Air Force learning services.

  • Integrated an AI chatbot into the USAF myLearning platform, the Air Force's enterprise learning system, including conversational experience design, an output-analysis process, and the command's AI adoption strategy.
  • Led delivery of Power Automate service-management workflows for an Air Force major command directorate: request intake, routing, approvals, and reporting built on the Microsoft Power Platform. Ran Microsoft Copilot in production from initial release, built in Copilot Studio, and authored the AI governance and acceptable-use framework covering agent approval, data-handling boundaries, and production review gates.
  • Produced DoDAF-compliant architecture views, capability maps, data models, and system-integration diagrams for cross-domain training platforms; drove modernization integrating AI, microservices, API-based analytics, and cloud-native components into myLearning.
  • Achieved the first-ever RMF Authority to Operate and USAF Program of Record for ITP(XR), an extended-reality maintenance-training platform.
  • Site Lead responsible for 19 contractors; ServiceNow enterprise architecture (ITSM, ITPM, CMDB, governance); executive briefings to senior Air Force leadership.
2014 – 2023

Enterprise Architect, USAF ADLS / TIMS / GTIMS

Data Systems Analysts, Inc., JBSA Randolph, TX. Progressed from systems engineering and test leadership to Enterprise Architect and Infrastructure Team Lead.

  • Enterprise Architect for USAF training-management systems serving 755K+ Airmen across 81+ sites (GTIMS: 60K users, 80K workstations).
  • Led GTIMS modernization to Azure GovCloud; stood up DevSecOps pipelines that cut deployment cycles 35%.
  • Delivered 200+ DoDAF-compliant artifacts: system views, data flows, data models, integration patterns, and security models.
  • Led ServiceNow implementation (ITSM, ITOM, CMDB); application-portfolio rationalization and shadow-IT consolidation; managed $1.2M budgets; headed AETC's Service Validation and Testing service.
  • Co-authored a 2019 AETC AI/ML pilot proposal: an ML scheduling engine fusing training data, weather feeds, and syllabi into risk-scored schedule recommendations with a Qlik leadership dashboard.
2002 – 2018

Earlier: Leidos, Raytheon, U.S. Air Force

  • Leidos: Senior System Engineer Manager for a data-center migration to AWS GovCloud; ServiceNow ITSM SME for CMDB, Change, and Incident Management. Earlier, depot engineering with predictive-failure metrics and trend analysis.
  • Raytheon: cut a security accreditation process from over six months to four weeks; deployed an insider-threat monitoring system into USAF networks ahead of schedule.
  • USAF (SSgt): administered a network-warfare test range of 5,000 workstations; engineered 23 Unix, Solaris, and Windows data-analysis systems processing 34 TB per day at 99% uptime; led client systems for 3,000+ machines. AF Achievement Medal with Valor.
2025 – present

Founder and Principal, ONSQ Enterprises / Ailura

AI product studio, publisher, and advisory. Also CTO of Doctor Marriage / Mapping Manhood.

  • Designed, built, deployed, and operates every system in the portfolio below, including sales, support, compliance, and app-store distribution.

Education and certifications

Portfolio

AI systems built and operated

Each system below was architected, coded, deployed, and is operated by Owen personally. The stacks listed are what actually runs in the code.

Ailura AI Receptionist

In production · paying customers

Multi-tenant AI front office answering voice, SMS, chat, and email for businesses. A tool-using agent books appointments against live calendars, quotes prices, relays messages, and escalates to humans, across all channels from one engine. Emotion AI (53-signal prosody detection) automatically escalates distressed callers. Tiered voice caching controls LLM and TTS cost; per-tenant OAuth calendar integrations; TCPA and A2P 10DLC compliance built in as code; automated nightly activity reporting.

StackOpenAI GPT-4o and Realtime API, agent tool-calling, Hume emotion AI, ElevenLabs, embeddings with RAG; Python, FastAPI, PostgreSQL, Redis, Twilio and Telnyx, Google and Microsoft OAuth; GCP Cloud Run, Fly.io.

Ailura Home Services

In production · live HVAC client

Multi-tenant field-service and e-commerce SaaS running a real HVAC company: missed call to AI text-back, conversational SMS booking agent, route-optimized dispatch, voice-dictated notes, AI-drafted Good/Better/Best quotes, text-to-pay, QuickBooks sync, and nightly KPI reports. Claude vision reads receipts and equipment nameplates into strict schemas with confidence gating. Explainable customer-opportunity scoring carries mandatory reasons and confidence on every row, with fairness guardrails coded in. A database exclusion constraint makes double-booking structurally impossible; the schema, not the prompt, is the final referee over the AI.

StackClaude agents and vision, Whisper transcription, explainable scoring; Next.js 15, React 19, Expo/React Native, Supabase Postgres with row-level security, 23 edge functions; Stripe Connect and Tap to Pay, QuickBooks OAuth sync, Twilio A2P 10DLC; Vercel, EAS.

Cheqer

Live · cheqer.vercel.app

AI-powered Bible word-study platform and graduate research artifact. A multi-turn Claude agent with four retrieval tools answers questions over a corpus of 425,000+ word tokens from eight ancient-text sources, using hybrid retrieval: exact lemma SQL where scholarly tagging exists, pgvector semantic search where it does not, with a deterministic citation-verification layer that structurally prevents hallucinated references. Retrieval quality is measured, not assumed: a reproducible evaluation harness reports precision@10 of 0.772 against a keyword baseline, with published per-case failure analysis.

StackClaude Opus 5 tool-use agent, OpenAI embeddings, pgvector hybrid RAG, IR evaluation (precision@k, recall), anti-hallucination guardrails; TypeScript, Expo, Supabase with 20 SQL RPC functions, Python ETL over eight corpora; Vercel.

Ailura Quant

Deployed · live forward test

Autonomous options-research and paper-trading engine running around the clock in the cloud. Black-Scholes pricing, greeks, and implied-volatility solving implemented from first principles; intraday regime classification; multi-factor candidate scoring; vectorized backtesting; and a read-only brokerage integration that coaches real trades against codified risk rules. Engineered with production reliability discipline: dead-man switches, crash-safe state recovery, audit logging, and 146 automated tests.

StackQuantitative modeling, backtesting and analytics, natural-language command interface; Python, FastAPI, pandas, numpy, SQLite with raw SQL, Alpaca and Schwab APIs; Docker, Fly.io.

NeuroDriver

Research · classroom-tested

Browser-based 3D "glass-box" driving simulator that teaches students how autonomous vehicles perceive and decide. Physically simulated LiDAR, thermal, camera, and audio sensors feed a hybrid AI, combining a TensorFlow.js deep Q-network, a safety behavior tree, and transparent utility scoring, whose every decision is inspectable live. Deployed with 97 middle-school students; the mixed-methods study is under review at ACM SIGCSE 2026.

StackTensorFlow.js DQN, reinforcement learning, explainable-AI interface, sensor simulation; React, Three.js, react-three-fiber, Vite.

Ailura WordPress product line

Shipped commercial products

Two commercial WordPress plugin families demonstrating end-to-end productization. Ailura Guru is a site chatbot with a five-provider LLM abstraction (Claude, GPT-4o, Gemini, Grok, and custom endpoints), encrypted key storage, knowledge-base retrieval, and CRM lead capture. Ailura Blog Writer (eight tagged releases, in production for a nationally distributed counseling-education platform) does deep-research generation with enforced JSON schemas, DALL·E 3 imagery, and automatic SEO integration. Licensing, free and pro editions, marketplace compliance, and release engineering included.

StackFive-provider LLM routing, structured outputs, DALL·E 3; PHP, WordPress, MySQL, Freemius licensing, release automation.

STRONGHOLD and Vigilant Spirit

Mobile · explainable AI

STRONGHOLD (Android, Google Play pipeline) is a recovery-aware AI strength coach that fuses wearable biometrics, including HRV baselines and workload ratios, with training data. Claude adjusts the plan through schema-constrained structured outputs that server-side guardrails re-validate: the model can adapt but never violate the safety envelope. Includes hand reverse-engineering of a rowing machine's Bluetooth protocol. Vigilant Spirit is an AI dream journal with genuine explainability, showing SHAP and LIME attributions to end users to demonstrate transparent consumer AI.

StackClaude structured outputs, Zod-constrained decoding, SHAP, LIME, biometric feature engineering; TypeScript, Expo, SQLite with Drizzle, Health Connect, BLE; Express, PostgreSQL.

Technology

Technology inventory

DomainTechnologies
LLM platformsAnthropic Claude (Messages API, vision, tool use, structured outputs); OpenAI (GPT-4o family, Realtime API, Whisper, DALL·E 3, embeddings); Google Gemini and Vertex AI; xAI Grok; custom and self-hosted endpoints; Azure AI Foundry; Microsoft Copilot and Copilot Studio
Agentic AIMulti-turn tool-use agent loops; structured outputs (JSON Schema, Zod-compiled formats); cross-provider tool-schema translation; model fallback and cost-tiered routing; guardrails as code (database constraints, citation verification, bounded action spaces); per-call token and cost ledgers; prompt-injection defenses; rate limiting
RAG & retrievalpgvector with ivfflat indexing; hybrid lexical and semantic retrieval; embedding pipelines; retrieval evaluation (precision@k, recall, lift over baseline); SQL-grounded context injection; vector-store content pipelines
ML & explainabilitySHAP; LIME; deep Q-networks (TensorFlow.js); spiking neural networks (96.95% accuracy at roughly 49% event retention); scikit-learn, PyTorch, TensorFlow; statistical learning in R; SAS; feature engineering (rolling baselines, z-scores, workload ratios); quantitative modeling (Black-Scholes, implied volatility)
Power PlatformPower Automate: automated service-management processes delivered for an Air Force major command directorate (intake, routing, approvals, reporting); Microsoft Copilot in production since initial release; Copilot Studio; Power BI; authored AI governance and acceptable-use frameworks for enterprise Copilot and agent adoption
Voice & telephonyTwilio (Voice, SMS, TwiML, Media Streams, signature validation, A2P 10DLC); Telnyx; OpenAI Realtime over media streams; ElevenLabs including voice cloning; Hume AI TTS and emotion; Google Cloud TTS/STT. Hand-built pipelines, no low-code wrappers
LanguagesPython; TypeScript and JavaScript; SQL and PL/pgSQL; PHP; PowerShell; Bash; R; SAS; C#; HTML/CSS
Data engineeringPostgreSQL; Supabase (RLS, auth, edge functions, cron, webhooks); SQLite; MySQL; Redis; Drizzle ORM; SQLAlchemy; schema design for multi-tenant systems of 37, 16, and 14 tables; exclusion constraints, GIN and ivfflat indexes, triggers, audit logs; multi-source ETL (XML, TSV, REST, and scraping across eight corpora); QuickBooks and wearable-data sync pipelines; idempotent pipeline design; pandas, numpy
Analytics & BIPower BI; Qlik Sense; SSRS; SAS Enterprise Guide; automated KPI pipelines with daily, weekly, and monthly rollups; custom production dashboards; model and retrieval evaluation metrics; mixed-methods study design
Cloud & DevOpsAzure GovCloud; AWS GovCloud; GCP (Cloud Run, Cloud SQL); Vercel; Supabase; Fly.io; Docker; Kubernetes; Terraform; GitLab CI/CD; Expo EAS with App Store and Google Play submission; secrets management and envelope encryption
Enterprise & governanceServiceNow (ITSM, ITAM/HAM/SAM, CMDB, ITOM, SPM, Change Management); DoDAF (200+ artifacts); TOGAF; RMF and ATO delivery; ITIL; Zero Trust; UAT planning; Sparx EA, Visio; compliance as code (TCPA, CAN-SPAM, GDPR, A2P 10DLC)
Role fit

What this means for a data-systems role

Core dutyTrack record
Requirements → data modelsDoDAF data models and capability maps for Air Force enterprise systems; three production database schemas designed from scratch; ServiceNow requirements backlogs and workflow specifications at AFLCMC
SQL & databasesHand-written PL/pgSQL across 60+ migrations; stored-procedure API layers; row-level security design; constraint-driven data integrity; index and performance tuning
ETL & pipelinesEight-source scholarly-corpus ETL; QuickBooks 15-minute sync; wearable-biometric aggregation; market-data ingestion; idempotency and auditability as standing design rules
Dashboards & reportingPower BI, Qlik Sense, and SSRS in Air Force settings; automated KPI reporting with rollups and live operations dashboards in his own production systems; SAS and R analytics training
Analysis & documentationAuthored a full ServiceNow platform user guide for an AF directorate; 38 documentation guides across his own products; UAT plans; founded AETC's service validation and testing practice
Stakeholder translationExecutive briefings to Air Force senior leaders; site lead for 19 contractors; onboarded real pilot customers; a published author and speaker who explains AI to non-technical audiences for a living
AI-augmented data systemsHis AI systems ship with evaluation harnesses, explainability columns, fairness guardrails, and cost ledgers: analyst discipline applied to generative AI
Research & writing

Research, publications, and teaching

Research (UTSA, M.S. Artificial Intelligence)

  • NeuroDriver classroom study (97 students), under review at ACM SIGCSE 2026
  • Explainable AI: SHAP analyses on COMPAS and Communities-and-Crime; a dream-classification XAI project
  • Spiking neural networks: 96.95% accuracy at roughly 49% event retention; a hyperdimensional associative memory architecture
  • Cross-corpus retrieval evaluation with published precision and recall results (Cheqer)
  • SELFPRINT (in progress): metamorphic probing of LLM self-representation across six models, roughly 13,800 responses

Publications and teaching

  • Image in the Machine (2026), on AI, human identity, and meaning; book, companion journal, and a 12-session study curriculum
  • Two additional published books; founder of ONSQ Enterprise Press (Amazon, IngramSpark, WooCommerce)
  • Six authored AI-literacy curricula spanning middle school through college and professional development
  • Keynotes and workshops on AI adoption for schools, churches, and businesses; weekly essays on Substack