FOUNDER · FINANCIAL CRIME & COMPLIANCE SME · BUILDER / ARCHITECT
SEE THE SYSTEM.
BUILD THE ANSWER.
I architect, build and scale systems for hard problems. My work has crossed investigations, operations, financial services, banking, financial crime, fintech and technology. The pattern is consistent: understand the whole system, design the operating model, build what is missing and make it work at scale.
HUMAN EXPERIENCE → OPERATIONAL INTELLIGENCE
SOURCE
30+ YEARS
investigation · systems · judgment
ORCHESTRATION LAYER
SPHERE
signals · context · memory · reasoning
SCROLL TO INITIATE ↓
OPERATING THESIS // 001
“ THE ADVANTAGE IS NOT HAVING MORE DATA. IT IS SEEING WHAT THE DATA MEANS TOGETHER.
PATTERN RECOGNITION · SYSTEMS THINKING · OPERATING JUDGMENT
BUILDER DNA // PATTERN DETECTED
THE JOB TITLES CHANGED.
THE PATTERN DIDN'T.
I have spent most of my life taking systems apart, understanding what makes them work, and building a better version.
01 / INVESTIGATION
SEE WHAT OTHERS MISS.
Evidence, interviews, surveillance, behavior, patterns and consequence. Learn to follow what is real, not what is convenient.
02 / OPERATIONS
BUILD FROM ZERO.
Shipping, receiving, purchasing, inventory, subcontractors, teams, procedures, workflows and businesses. Structure turns effort into scale.
03 / FINANCIAL SYSTEMS
UNDERSTAND THE MONEY.
Banking, financial services, insurance, KYC, AML and regulated products created the financial context behind the investigations.
04 / FINTECH + BaaS
UNDERSTAND THE ECOSYSTEM.
Fintechs, sponsor banks, middleware, partner oversight and financial-crime operations reveal where intelligence breaks across organizational boundaries.
VENTURE HISTORY // SELECTED SIGNALS
BUILD. LEARN. EXIT. FAIL. BUILD AGAIN.
No résumé timeline. Just the experiences that changed how I build.
FOUNDER SIGNAL // THE LONG ARC
I DIDN'T START WITH SOFTWARE.
I STARTED WITH THE PROBLEM.
The technology came later. First came learning how criminals behave, how evidence connects, how businesses operate, how financial systems move money, how compliance functions break under scale, and how disconnected organizations lose context.
Gryphon Sentinel is the accumulation of those experiences — not an AI idea looking for a financial-crime use case.
OPERATING PATTERN
UNDERSTAND → CONNECT → QUESTION → BUILD
INVESTIGATION
OPERATIONS
BANKING
FINCRIME
BaaS
AI + DATA
TRANSFERSPHERE
One of the first real jobs: helping build operations inside a startup making dye-pack security technology used against bank robbery.
Private investigations and law enforcement taught evidence, behavior, pattern recognition, consequence and how bad actors adapt.
Startups, businesses, teams, exits and one bankruptcy built a bias toward execution, resilience and learning from what actually happens.
Banking, securities, insurance and financial crime added the regulatory, money-movement and customer context behind the investigations.
Working inside the ecosystem exposed the deeper problem: intelligence is fragmented across teams, platforms and organizations.
Turn the accumulated operating judgment into a platform that can help institutions see more, remember more and make better decisions.
SYSTEMS I BUILD // FROM CHAOS TO STRUCTURE
ARCHITECT THE MODEL.
BUILD IT. SCALE IT.
Sometimes the problem is a department. Sometimes it is a workflow, a reporting structure, a case process, a partner-oversight function or a technology layer. The common pattern is the same: understand the real problem, architect the operating model, build the missing pieces, then make the system repeatable and able to scale.
BUILD_01 // UNIT ARCHITECTURE
DESIGN THE UNIT.
NOT JUST THE TASKS.
A strong function needs more than analysts. It needs roles, escalation paths, ownership, handoffs, governance, reporting, metrics, quality controls and a clear reason for existing.
ROLES + RESPONSIBILITIES
ESCALATION MODEL
WORK QUEUES
QUALITY + GOVERNANCE
INTERACTIVE CONCEPT // UNIT ARCHITECTURE
LIVE BLUEPRINT
FUNCTION BLUEPRINT
INTAKEREVIEWESCALATEREPORT
SELECTED EVIDENCE // BUILDER PATTERN ACROSS DECADES
NOT ONE JOB. A REPEATED OPERATING PATTERN.
Selected public-safe examples showing the same pattern across technology, investigations, fintech, sponsor banking and the current independent build.
Built operating systems around bank-security technology: purchasing, inventory, shipping/receiving and subcontractor operations.
Helped build the operating infrastructure of an early-stage technology company as it moved from startup toward scale.
Built a licensed investigations company from zero, including the operating model, team, evidence standards and quality controls.
Helped architect and build partner-risk operations, evidence workflows, escalation structures and high-volume legal-order processing.
Built financial-crime operating structures and AI-enabled workflows across fraud, intelligence, high-risk review and governance.
Architecting and building an independent financial-crime operational-intelligence platform across the bank–fintech ecosystem.
FOUNDER STATEMENT // PERSONAL OPERATING SYSTEM
I HAVE NEVER BEEN VERY INTERESTED IN WORKING AROUND A BROKEN SYSTEM. I WANT TO UNDERSTAND WHY IT IS BROKEN — THEN BUILD THE BETTER ONE.
I started trying to build things long before I had credentials for it. My first company was at 19. The degree came decades later. In between came startups, investigations, businesses, banking, financial crime, two exits, a bankruptcy, and a lot of systems that taught me something.
Gryphon Sentinel is not a departure from that history. It is what that history has been leading toward.
OPERATING PRINCIPLES // HOW I APPROACH THE BUILD
THE TECHNOLOGY SHOULD
MAKE THE THINKING BETTER.
Do not automate a bad process simply because automation is available.
An alert, case, customer or dataset is usually only one piece of the operating system around it.
Rules, queries, known history and deterministic logic should solve what they can before AI is asked to reason.
A closed investigation should become future context, not forgotten history.
Machines should assemble, connect and accelerate. Consequential decisions still need accountable human authority.
AI + TECHNOLOGY // HOW I BUILD
AI ISN'T THE SKILL.
WHAT YOU CAN BUILD WITH IT IS.
I use AI as an engineering and operating force multiplier. Domain expertise defines the problem and the decision architecture. Then the right combination of models, data, APIs, automation, development tools and human judgment turns that architecture into something usable.
Gryphon Sentinel is the clearest example: an independently architected multi-interface React/Vite platform moved from domain concept to working demo, API-connected intelligence and cloud deployment without an engineering team.
VIEW FULL TECHNOLOGY + AI PROFILE →01DOMAIN EXPERTISEwhat actually matters
→
02ARCHITECTUREoperating model + decisions
→
03AI-ASSISTED BUILDcode + workflows + automation
→
04TEST + DEPLOYmake it real
CLAUDE CODECOWORKMCPCHATGPTHATZ AI
REACT / VITEGITHUBCLOUDFLAREAPIsSNOWFLAKE
POWER BIUNIT21UNITFOOTPRINTSARDINE
ALLOYHEYGENELEVENLABS
RECENT PROOF // AI-ENABLED FRAUD WORKFLOWS · MULTI-AGENT DEVELOPMENT · API-CONNECTED PRODUCT BUILD · PRIVATE GS DEMO
SYSTEM VIEW // PATTERN RECOGNITION
THE SIGNAL IS OFTEN
IN THE RELATIONSHIP.
Most systems present one alert, one customer, one case or one dataset at a time. I naturally look across the environment to understand how the pieces influence each other — and what nobody is asking yet.
WHOLE_SYSTEM_VIEW // SIMULATION
SYSTEM INTERPRETATION
ISOLATED SIGNALS
Eight facts. No shared context.
SELECT “SEE THE SYSTEM” TO REVEAL THE HIDDEN STRUCTURE.
Move beyond the assigned alert or workflow and understand the operating environment around it.
Look for dependencies, history, entities, incentives and interactions that change what the individual facts mean.
The most valuable question is often the one the existing system was never designed to ask.
Convert the understanding into a process, operating model, control, product or technology that can scale.
BACKGROUND SIGNALS
ENGINEERING STUDIES + SCHOLARSHIP // UT AUSTIN COCKRELL
FORMER FINRA // 6 · 7 · 63 · 66
MULTI-STATE INSURANCE LICENSURE
CAMS // FINANCIAL CRIME
MILITARY + LAW ENFORCEMENT
FOUNDER THESIS // SYSTEM DIAGNOSIS
MORE DATA ISN'T THE ANSWER.
MORE AI ISN'T THE ANSWER.
The advantage comes from knowing what matters, how it connects, what question to ask, which tool should answer it, and when human judgment must decide.
DATA≠INTELLIGENCE
AI≠EXPERTISE
TECH≠JUDGMENT
SME + DATA + TECH + AI→OPERATIONAL INTELLIGENCE
CURRENT STATE
FRAGMENTED
information everywhere
BANK
FINTECH
MIDDLEWARE
CASE SYSTEMS
ALERTS
DOCUMENTS
EXTERNAL INTEL
PEOPLE
DECISION THESIS // UNDERSTAND BEFORE EXIT
MORE DEBANKING ISN'T THE ANSWER.
BETTER UNDERSTANDING IS.
Some relationships absolutely need to end. But account closure should not become the default substitute for understanding the customer, the behavior, the history, the relationships and the actual source of risk.
Better understanding creates better decisions. Sometimes that decision is exit. Other times it may be a more precise intervention: restrict, monitor, escalate, remediate, educate or redesign the control around the risk.
THIS IS A POINT OF VIEW ABOUT DECISION QUALITY — NOT A CLAIM THAT EVERY ACCOUNT SHOULD STAY OPEN.
BETTER DECISION MODEL
01UNDERSTANDcustomer · history · relationships · context
→
02DECIDEactual risk · proportional response · accountable judgment
→
03INTERVENEmonitor · restrict · escalate · remediate · close
BLUNT MODEL
ALERT → RESTRICT → CLOSE
BETTER MODEL
UNDERSTAND → DECIDE → INTERVENE
WHY NOW // OPERATING PRESSURE
THE INDUSTRY IS ADDING
CAPABILITY FASTER THAN CONTEXT.
More tools, more models, more data and more automation do not automatically produce a better operating system. The constraint increasingly becomes interpretation, orchestration and institutional memory.
Models can accelerate work. They cannot substitute for a domain expert defining what the system should understand, ask, preserve and escalate.
Organizations can build enormous datasets and still fail to convert them into connected operational intelligence.
Bank, fintech, middleware, vendors and consumers can all touch the same risk while holding different pieces of the truth.
The goal should not be to remove judgment. It should be to stop wasting judgment on work the system could have assembled, connected and remembered.
INTELLIGENCE BRIEF // WHY SYSTEMS FAIL
THE PROBLEM ISN'T
A LACK OF TECHNOLOGY.
ASSESSMENT // ACTIVE
FAILURE_01 // FRAGMENTATION
THE DATA EXISTS.
THE PICTURE DOESN'T.
Alerts, customer history, documents, devices, partner communications, prior decisions and external intelligence may all exist — but not in the same operating context. Analysts reconstruct the picture by hand, one case at a time.
IMPACT duplicated work · inconsistent decisions · missed relationships
THE DIFFERENCE // SME → SYSTEM
KNOWLEDGE ISN'T A DATASET.
IT'S HOW YOU INTERPRET ONE.
The objective is not to pour decades of experience into a model. It is to encode the operating judgment behind the questions: what matters, what connects, what is missing, what should happen next, and when a human must decide.
HUMAN SME
EXPERIENCE
investigation · banking · fraud · AML · operations · BaaS
ENCODE OPERATING JUDGMENT
INTELLIGENCE LAYER
SPHERE
context · orchestration · memory · reasoning
CURRENT BUILD // ONE CHAPTER OF THE STORY
GRYPHON SENTINEL™
The current and most ambitious expression of the operating pattern: see the system, architect the model, build the intelligence layer, and design it to scale across organizations.
CURRENT BUILD // THE LATEST EXPRESSION OF THE PATTERN
GRYPHON
SENTINEL™
Operational intelligence for financial crime.
INSTITUTIONAL MEMORYCROSS-ORGANIZATION INTELLIGENCEORCHESTRATION-FIRST REASONING
PRIVATE DEMO // ACCESS REQUIRED
gsi.demo.gryphonsentinel.com ↗
LIVE PATTERN LAB // SYNTHETIC DATA
THE FACTS LOOK NORMAL.
UNTIL YOU CONNECT THEM.
This is a real front-end interaction using fictional financial-crime data. It is not an AI demo and it does not call an external service. The point is simpler: show how isolated facts can become a different problem when relationships, history and context are viewed together.
OBSERVED
SHARED ATTRIBUTE
PRIOR HISTORY
ESCALATION
CURRENT BUILD // GRYPHON SENTINEL™
TURN INFORMATION
INTO INSTITUTIONAL INTELLIGENCE.
Gryphon Sentinel is being built as an operational intelligence platform for financial crime — designed around institutional memory, cross-organization intelligence and orchestration-first reasoning.
01UNIFYsignals, history, decisions and outcomes
02CONNECTentities, relationships and organizations
03ORCHESTRATErules, data, tools, intelligence and AI
04REMEMBERpreserve institutional knowledge
05DECIDEgive humans better context and judgment
SPHEREINTELLIGENCE ORCHESTRATION
SENTINEL FILESpersistent work + case intelligence
ENTITY + NETWORKrelationships · context · history
INSTITUTIONAL MEMORYdecisions · outcomes · learning
DATA FABRICunify · normalize · protect
ECOSYSTEMbank · fintech · middleware · consumer
PRODUCT SURFACES // PLACEHOLDER SYSTEM
ONE INTELLIGENCE CORE.
MULTIPLE OPERATING SURFACES.
Real Gryphon Sentinel screens will drop into these frames later. For now, the structure shows how the platform can present the right operating view to the right participant without turning the public site into a product manual.
ASSET MODE // PLACEHOLDERS
SCREEN SWAP // READY
SURFACE_01 // SPONSOR BANK COMMAND
FINANCIAL-CRIME OPERATIONS
AS ONE CONNECTED SYSTEM.
A bank-side operating surface spanning fraud, FIU, CIU/EDD, governance, partner oversight, quality and executive visibility while preserving role-specific views.
GS SCREEN // BANK COMMAND
PLACEHOLDER
REAL PRODUCT SCREEN RESERVED
GS SCREENSENTINEL FILEPLACEHOLDER
PERSISTENT WORK UNIT
Evidence, communications, decisions, relationships and outcomes survive the life of the alert.
GS SCREENSPHEREPLACEHOLDER
ORCHESTRATION LAYER
Use the simplest reliable source of truth first. Apply AI when reasoning actually adds value.
GS SCREENNETWORKPLACEHOLDER
CONNECTED INTELLIGENCE
Entities, devices, accounts, counterparties, cases, outcomes and cross-portfolio relationships.
GS SCREENEXECUTIVEPLACEHOLDER
DECISION VISIBILITY
Operational health, exposure, partner performance, staffing, trends, controls and emerging risk.
ECOSYSTEM MODEL // CONNECT WITHOUT COLLAPSING BOUNDARIES
THE SAME RISK CAN EXIST
IN FOUR DIFFERENT WORLDS.
Gryphon Sentinel is designed around the reality that sponsor banks, middleware providers, fintechs and consumers can each own different information, responsibilities and permissions. Intelligence should connect the picture without pretending those boundaries do not exist.
INTELLIGENCE LAYER
GS
orchestrate · remember · connect
PRIVACY WALL
PERMISSION BOUNDARY
SPONSOR BANK // Enterprise-wide oversight, accountability, escalation and institutional memory.
GRYPHON SENTINEL // OPERATING MODEL
NOT ANOTHER DASHBOARD.
A SYSTEM THAT REMEMBERS.
This conceptual console shows the operating idea: a signal should not die inside an alert. It should become connected context, persistent work, institutional memory and a better human decision.
GS // INTELLIGENCE OPERATIONS
ENV // CONCEPTHUMAN AUTHORITY // ON00:00:00
STAGE_01 // SIGNAL INTAKE
ONE SIGNAL ENTERS.
THE SYSTEM WIDENS THE FRAME.
A referral, alert, partner communication or external signal becomes a persistent work object instead of an isolated event. Context begins accumulating immediately.
01 SIGNAL06 CONTEXT SOURCES00 LOST HISTORY
THE PRODUCT IS THE OPERATING INTELLIGENCE.
LIVE INTELLIGENCE LAB // FRONT-END PROTOTYPE
DON'T SAY YOU KNOW TECH.
MAKE THEM USE IT.
SYSTEM ONLINE
WT_INTELLIGENCE_TERMINALLOCAL // CHECKING LIVE SERVICE
ENTITY RESOLUTION // SIMULATIONLIVE
ABC INDUSTRIAL LLC
OWNER
DEVICE
IP ADDRESS
ACCOUNT
COUNTERPARTY
SELECT AN ENTITY TO INSPECT RELATIONSHIPS.
COLLABORATION // OPEN
THE RIGHT CONVERSATION
CAN CHANGE THE BUILD.
The right problem can become a product, an operating model, a deployment, a partnership or an entirely new build. I am interested in the work where deep domain knowledge and technical ambition actually meet.
BUILDARCHITECTPARTNERDEPLOYINVEST
START A CONVERSATION
VIEW PUBLIC BUILDER PROFILE
OPEN VECTOR // THE NEXT BUILD DOESN'T HAVE ONE SHAPE
THERE ARE MULTIPLE WAYS
THE RIGHT PEOPLE CAN WORK TOGETHER.
Founder. Operator. Design partner. Strategic customer. Institutional build. Advisor. Investor. The label matters less than whether the problem, people and incentives are aligned.
WMTBUILD
SELECT A VECTOR // OPTIONALITY IS INTENTIONAL
ACCESS CENTER // ONE PLACE FOR EVERYTHING
FOUNDERS DON'T JUST NEED A SITE.
THEY NEED A COMMAND CENTER.
This site can become the single place for the materials that matter: founder briefs, presentations, product demos, screenshots, selected documents, architecture summaries, investor material and private working assets — all organized behind controlled access.
FOUNDER + COMPANY
Founder story, one-pagers, founder briefs, biography material and public/company overview assets.
PRODUCT + DEMOS
GS screenshots, walkthroughs, demos, architecture snapshots, private product overviews and use cases.
PRESENTATIONS + DOCUMENTS
Decks, PDFs, presentations, founder notes, selected work artifacts, sanitized case material and reference docs.
PARTNER / INVESTOR ACCESS
Private access paths for strategic partners, design partners, clients, investors and other serious conversations.
PRIVATE VAULT // STRUCTURE PREVIEW
CURATED IN PUBLIC.
DEEPER MATERIAL IN PRIVATE.
The public side should persuade. The private side should deliver the substance. This keeps everything in one place without turning the website into a cluttered file cabinet.
ENTER ACCESS CENTERPUBLICSTORY
PRIVATEDEMO
PRIVATEDOCS
PRIVATEINVESTOR
ACCESS GATE
SELECTED SIGNALS // NOT A RÉSUMÉ
CAMS
ACAMS CHAPTER BOARD
FORMER FINRA 6 · 7 · 63 · 66
UT AUSTIN COCKRELL // SCHOLARSHIP
LAW ENFORCEMENT
MILITARY SERVICE
2 EARLY-STAGE TECH COMPANIES
2 BUSINESS EXITS
FIELD NOTES // THINKING IN PUBLIC
IDEAS WORTH
ARGUING ABOUT.
AI IS NOT INTELLIGENCE.
Why adding a model to a broken operating system does not create expertise.
THE INSTITUTIONAL MEMORY PROBLEM.
Financial institutions know more than their systems can remember.
THE BaaS INTELLIGENCE GAP.
Bank, middleware and fintech each see a different piece of the same risk.
BUILDERS NEED DOMAIN EXPERTS.
The dataset is only the beginning. The hard part is knowing what to do with it.