2012 to 2019
National statistical agency economist
Gold-standard validation for production survey classification systems, microdata QA on a team basis, and authored peer-reviewed workplace injury research (MLR, 2017).
About Deep Person LLC
Deep Person LLC is a veteran-owned U.S. small business that helps organizations turn scattered information into custom AI orchestration, operations automation, generative media pipelines, and actionable custom software, generalizing a decade of federal analytics and production systems work.
Founder background
2012 to 2019
Gold-standard validation for production survey classification systems, microdata QA on a team basis, and authored peer-reviewed workplace injury research (MLR, 2017).
2019 to present
GenAI-integrated Python pipelines, document ingestion, thematic analysis for safety operations, and operations research (ElasticNet, procurement and lifecycle cost modeling).
2020 to present
GhostOffice, Deep Personality, shop and licensing infrastructure, and custom orchestration for clients.
Executed work
Organization names are omitted from public marketing copy. These describe capability patterns from production systems. The same integrator model Deep Person applies to client projects.
Built in-house Python pipelines integrating DoD GenAI APIs with configurable feature extraction from operational incident records. Language-model categorization clusters themes for leadership Pareto analysis; OCR plus model orchestration converts image PDFs to structured JSON; outputs feed brief-ready deliverables.
Supported gold-standard validation and quality testing for production logistic regression systems that classify large federal survey records (NAICS, occupation coding). Team contributor on multi-year microdata harmonization and QA for annual production pipelines.
ElasticNet regression and econometric forecasting applied to multi-year procurement modeling and lifecycle cost analysis from asset feature data (e.g. hull length, beam, engines). Integrates quantitative engineering into software development.
Data integrator
Deep Person creates value by connecting datasets, creating new datasets where needed, and building maintainable software around the combined information. GhostOffice demonstrates the orchestration layer; Deep Personality demonstrates the structured data product layer. Both inform how client systems are designed.
Growing businesses, larger enterprises, research teams, and operations groups with scattered data, agent workflow needs, local media generation pipelines, manual review work, or recurring anomalies.
Data visibility, exception handling, operational workflows, reporting, and the repeatability of analytical judgment.
Data handling and engagement
Cloud, hybrid, and local-only patterns. GhostOffice supports fully offline Ollama mode; client projects can target your VPC, on-prem, or approved cloud environments.
Scoped access, NDA on request, and minimal retention for discovery work. Sensitive operational data stays in environments you control unless you specify otherwise.
Discovery conversation first, then a scoped proposal with timeline and deliverables. Project inquiry captures data sources, constraints, and review steps up front.
Products
Desktop AI orchestration workbench: visual agent swarms, document and table workflows, entity extraction, Vertex AI and Ollama. Trial, licensing, and CI releases.
See GhostOfficeLive multi-provider language-model product mapping user responses across scientific trait frameworks on AWS.
Visit live appNext-generation platform on Next.js, Supabase, Prisma, and Vercel AI SDK for agentic features and persona automation.
Try the betaOrchestration, data integration, and operations automation scoped to your workflow. Start with a project inquiry.