global patents
AI/ML security, identity, cryptography, fraud, and platforms
AJIT GADDAM
Ajit Gaddam
Engineer, executive, and inventor working across artificial intelligence, cybersecurity, identity, and fraud.I currently lead Fraud, AI & Trust Platforms at HealthEquity. Before that, I built security and fraud systems at Wells Fargo, Visa, Progressive, a startup of my own, and Google.
This is my personal index: work, inventions, writing, and small things I am building outside the job.
BUILD SIGNAL
CURRENTLY
Fraud, AI & Trust Platforms
Working on AI-native fraud defense, autonomous-system trust, and platforms where models can take action—not only make suggestions.
- AT
- HealthEquity
- ALSO
- Inventing, writing, advising, and building ajit.ai
ACTIVE FIELD · TRUSTVisa → Wells Fargo → HealthEquityZero trust to accountable AI systems
published books
Hadoop in Action and Learning Hadoop Security
years building
research, startups, large-scale products, and technical leadership
writing in public
security, systems, identity, data, and the changing web
PATH HERE
A career spent close to consequential systems.
- 01CMU
- 02Google
- 03SkunkLabs
- 04Progressive
- 05Visa
- 06Wells Fargo
- 07HealthEquity
BUILDS
Small problems, opened all the way.
01 / IOS + IPADOS + MACOS
Kids Art: Coloring Pages
The family app I wanted when a child asked for one specific coloring page and school artwork kept turning into a paper pile. It makes, prints, scans, and keeps the work without ads or child accounts.
02 / MACOS + STORAGE INTELLIGENCE
Storage Insight: Reclaim Space
The storage recovery app I needed when my own Mac had less than 1 GB free. It explains what is growing, puts the safest meaningful decision first, and proves what changed.
03 / FRAUD + VOICE AI
Fraud-Fighting AI Granny
A voice agent designed to consume a scammer’s time without putting a real person or real personal information into the conversation.
AI / ML + AUTONOMOUS SYSTEMS
From autonomous-systems research to AI products operating under real pressure.
The through-line is turning frontier capability into systems that can survive adversaries, customers, and scale.
Autonomy was the starting point.
My path began in AI and robotics at Carnegie Mellon, with work connected to the DARPA Grand Challenge. Today the system is software: agents that need bounded authority, evidence, and accountability.
Models became systems worth defending.
Research and inventions on untrustworthy models, behavioral signals, and adaptive defense treated machine learning as an attack surface before AI security became a category.
Research matters when it survives production.
A decade building ML-driven cybersecurity products at Visa, followed by fraud and generative-AI platforms in banking and healthcare, kept models close to customers and operating risk.
Prototype energy. Product discipline.
I have built as a founder, inside global platforms, and outside the job—keeping the loop from problem through architecture, release, customer reality, and operation visible.
THE LONG THREAD
Earlier writing, read as precedent—not a news feed.
IN PUBLIC
Interviews, talks, patents, case studies, and public service, with a source attached.