Breadth is the edge.

Enterprise AI transformation leader. I own global generative-AI strategy, governance, and scaled deployment across The North Face, Vans, Timberland, and Dickies. I've taken AI from proof-of-concept to global production — CAD-to-render pipelines producing tens of thousands of QA-reviewed assets, AI on-model product imagery for The North Face, fully AI-produced social campaigns for Vans and Dickies, and AI-personalized wholesale decks and lookbooks — all under brand, legal, and IP governance I helped establish.

Results: 2× speed-to-market and an immediate 30% cut in content-production costs, on a roadmap toward 80%+.

• GenAI strategy
• Governance
• CAD-to-render
• On-model imagery
• Wholesale personalization

Bootstrapped and funded by my own digital-services agency (marketing, development, and consulting). Visionary and leading contributor — not sole builder — with a team of 10 across a 25-brand portfolio. Indra drove 30%+ YoY revenue lifts for 50 e-commerce brands.

Client credibility included TaylorMade, The North Face, Smartwool, Vans, AShoc, Kassia Surf, Need Essentials, Colby+, and Infinity X1 — the sole white-label outdoor-lighting provider for Costco, Walmart, Home Depot, and Lowe's.

• Growth SaaS
• E-commerce
• Attribution
• Personalization

Built algorithms that adjusted ad spend in real time on live performance across hundreds of Meta / Facebook audiences — well before Meta's own algorithms matured to do the same. Proof-first: I hand-coded a custom Chart.js dashboard to monitor a manual ("Mechanical Turk") pilot to prove the algorithm out. The evidence was strong enough that we hired a developer to productionize it.

Younity required users to install both a mobile and desktop app and connect them, so "engaged users" was the real, hard metric. I diagnosed and fixed a technical attribution problem (via Apsalar) that had been obscuring the true user numbers — a data-integrity fix, told professionally.

Outcome: ~0 → hundreds of thousands of engaged users over roughly two years, with ~30% MoM engaged-user growth.

• Attribution
• Real-time bidding
• Cross-device
• Data integrity

To bring something distinctive to the Vans interview, I analyzed Vans.com, spotted the discovery problem — thousands of products, impossible to browse — and self-spec'd a dynamic discovery engine: a left/right swipe interface on attributed product imagery, using the normal equation client-side to build an affinity profile across nuanced trend dimensions (well beyond color and attribute tags). I walked into the interview with a working concept.

Then depth: consumer lifecycle management across thousands of loyalty-app data points — frequency, type, favorite band, and more — a personalization gold mine. I worked directly with the Director of Personalization before joining the data-science team.

I became so convinced that hyper-personalization was the next wave — and, spurred by COVID — that I left Vans in early 2020 to start two AI companies, roughly two weeks before the pandemic shift. Betting on AI in 2020, pre-ChatGPT.

• Personalization
• Data science
• A/B testing
• Loyalty data

Cross-functional product management, product design, and strategic account management inside established building-products companies. This is where the breadth throughline was set — working from customer discovery through spec through delivery, and owning the strategic account relationships that turn a product into a business.

• Product management
• Product design
• Strategic accounts

Autonomous indoor-growing systems: ingest climate and nutrient observations, apply multivariate regression to tune climate, water, and nutrient inputs, and compute a growth index from NDVI and LiDAR imagery. Founded alongside the 2020 AI bet — early conviction applied to a physical-world problem.

botan.ai.app

• Computer vision
• NDVI / LiDAR
• Multivariate regression
• IoT