Case studies.
Selected work across enterprise programs, product builds, and community platforms.
Enterprise AI, shipped in 90 days.
Context. Inside one of the world's largest financial institutions, Alec built and led delivery of an enterprise AI sanctions-screening solution for financial crime compliance.
What Alec led. The full product lifecycle: requirements gathering, AI opportunity identification, product strategy and design, UI/UX, development, automation and agentic AI, testing, and enterprise implementation. He led cross-functional teams through the build, trained teams and stakeholders on AI adoption, and presented the strategy and business value to executive leadership.
Result. The solution automated work that previously required about 180 employees. At roughly $80,000 in average annual compensation per role, that represents about $14.4M in annualized labor-cost equivalent, taken from requirements to enterprise delivery in about 90 days.
Global enterprise, 160% more throughput.
Context. A $50M+ enterprise technology portfolio inside one of the largest financial institutions in the world, spanning compliance engineering and AI-enabled financial crime technology, with global delivery teams.
What Alec led. 3+ Agile engineering teams and 50+ engineers, QA professionals, architects, and analysts, through Scrum leadership, Release Train Engineering, and program leadership.
Result. A 160% productivity improvement in 7 months and over $10 billion in operational efficiencies and business value, achieved in one of the most regulated delivery environments in the world.
The automation framework that started it all.
Context. As a QA automation engineer, Alec built an automation framework from scratch, including 70+ automated test scripts in five months.
Result. 60% reduction in test execution time, automated validation of 1,000+ query results down to row and cell level, a team of 6 QA engineers supported, 5 teams trained, and a critical showstopper defect caught before it reached production.
This is the engineering DNA behind every automation XConvergence ships today.
Autonomous AI.
Context. Autonomous AI is a fully autonomous AI-powered operating system for solopreneurs and service business owners.
Status. In active development. Earlier product work includes Swipe Savvy, a web and iOS product that secured funding about 60 days after launch.
Orlando Magic Innovation Challenge.
Context. Alec and his team entered the Orlando Magic Innovation Challenge with an AI basketball coach, applied AI for player development and the fan experience.
Result. Voted the #1 idea of the challenge, with the creation earning a shout-out from NBA Hall of Famer Grant Hill.
The AI Strategist Academy.
Context. A community teaching AI strategy, entrepreneurship, and real-world implementation to founders and operators.
Result. 1,050+ AI specialists trained and counting.
The same inputs stopped giving you the same outputs.
Whether you carry the whole thing yourself or run a team of twenty, the pattern is the same. The calls that filled your calendar last year don't fill it now, and the businesses taking that work installed systems while everyone else was still watching videos about them. Waiting is a decision too. With the systems running, this is an ordinary Tuesday:
- The missed call at 7pm gets answered, sorted, and booked while you're under a house or sitting with a client.
- The quote still in your drafts goes out the same day, then chases itself until someone answers.
- The client who went quiet in March gets a reason to come back, without you remembering to send it.
Free. Every tool named, every monthly cost shown. Build it yourself, or don't build it at all.
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