David Wolf · Project Use Case
AI SECURITY · PRODUCT SECURITY · RIVERBANKS / INTERNAL PRODUCT
RiverBanks / Internal Product
EMPOWER LIWC Psychometric Framework Factory
A psychometric product engine combining LIWC-compatible text analysis, 300+ dictionaries, WASM/Go/Rust runtimes, personality prediction, survey...
Built EMPOWER as a psychometric framework factory and personality-intelligence engine, combining LIWC-compatible dictionary analysis, 300+ lexical dictionaries, tiny Go containers, WASM binaries, later Rust/WASM engines, seven...
Client
RiverBanks / Internal Product
Engagement Type
Internal product and research buildout
Period
2023–2026
Role
Principal Architect / Psychometric Systems Architect / AI Product Engineer
Focus Areas
LIWC-Compatible Text Analysis, Psychometric Frameworks, 300+ Dictionaries, WASM Runtime
The Research Narrative
Strategic Problem
The challenge was building a practical framework factory rather than a single static assessment. The system needed to support multiple psychometric families, multilingual survey variants, lexical/dictionary...
What David Did
Built a LIWC-compatible text-analysis engine using 300+ lexical dictionaries to support psychometric and behavioral language analysis.
What Became Clearer
Created a substantial psychometric intelligence platform rather than a single survey.
Consulting Proof
This is evidence of turning messy security telemetry into explainable dashboards, alert-quality improvements, and executive-ready operating views.
The Context
EMPOWER sits inside the broader RiverBanks / workforce-development / talent-intelligence product direction. It draws from research into quantified psychometric profiles, job fit, team fit, culture fit, personality inference, SDR battle cards, recruiter outreach optimization, LMS packaging, and AI-generated advisory reports. The system is related to, but broader than, the psychographic job-fit engine because it includes survey generation, LIWC-compatible lexical analysis, education/training packaging, and dynamic coaching personas.
The Challenge
The challenge was building a practical framework factory rather than a single static assessment. The system needed to support multiple psychometric families, multilingual survey variants, lexical/dictionary analysis, local execution, coaching reports, role matching, team matching, and LMS-style distribution without becoming a pseudoscientific black box or brittle prompt-only product.
What I Did
- •Built a LIWC-compatible text-analysis engine using 300+ lexical dictionaries to support psychometric and behavioral language analysis
- •Packaged early runtime components into tiny Go containers and WASM binaries, with later movement toward reusable Rust/WASM engines
- •Designed EMPOWER as a framework factory capable of generating and adapting multiple psychometric survey families
- •Created or planned seven psychometric survey families covering workplace behavior, motivation, personality, leadership, team fit, communication, and development themes
- •Implemented translation and reverse-translation workflows so survey content could be adapted across markets while preserving meaning
- •Connected psychometric outputs to dynamic LLM report agents such as career counselor, relationship counselor, organizational psychologist, leadership advisor, and manager/team guidance personas
- •Used personality and profile outputs for team psychometric matching, SDR battle cards, recruiter outreach optimization, and career guidance
- •Explored role matching against frameworks such as ONET and NICE so psychometric profiles could connect to real work categories
The Outcome
Created a substantial psychometric intelligence platform rather than a single survey.
Research Outcomes
Signal Quality
Improved the trustworthiness of operational security signals
Operational Clarity
Translated complex security data into clearer operating views
Stakeholder Visibility
Made technical risk and status easier to explain
Operational Impact
Turned raw telemetry into actionable security intelligence
Capabilities Demonstrated
Executive Reporting
Security data translated for leadership
Operational Reporting
Actionable views for security operations
Security Analytics
Signal investigation and event analysis
IAM / Access Control
Identity telemetry and access insights
SIEM Alert Debugging
Noise reduction and signal validation
Dashboard Development
Operational and executive views
Telemetry Normalization
Consistent and trusted data
Public-Safe Evidence
Shareable insights without sensitive data
Key Deliverables
- •EMPOWER psychometric framework architecture
- •LIWC-compatible text-analysis engine
- •300+ dictionary lexical analysis layer
- •Tiny Go container and WASM binary runtime patterns
- •Rust/WASM migration architecture
- •Seven psychometric survey-family model
- •Translation and reverse-translation workflow
- •Dynamic LLM coaching report agents (career counselor, leadership advisor, organizational psychologist, manager/team guidance)
Tools & Technologies
Consulting Translation
The reusable pattern is not Disney-specific: normalize fragmented security telemetry, debug low-signal alert behavior, build trusted operating views, and give leadership evidence they can act on without exposing sensitive systems.