I turn company-level bets into products people trust.

I'm Ayon, a product leader with roots in design and behavioral research. I work across strategy, customer discovery, and execution to bring complex technology to market.

Ayon Bhattacharya

Ownership from insight to market.

As an early employee at Eve, I helped build AI products on the company's path to a $1B+ valuation. I led product and design for an AI intake system for law firms, taking a company-level bet from discovery through design, launch, iteration, and go-to-market enablement, bringing together voice AI, live call support, and lead intelligence.

My work spans customer research, product requirements, roadmap sequencing, and evaluating whether an AI experience is ready to ship. I work with engineering, sales, marketing, and customer success to connect what we build with how customers adopt it.

In the beta, 50% of callers chose the AI assistant over waiting for a person. That choice matters: customers have to trust a product enough to put it to work.

Explore the Eve case study

Product choices are business choices.

Making the economics work at Treasure

As founding designer, I advocated for self-serve onboarding because a high-touch sales model didn't fit the economics of serving small businesses. I worked with the CEO, CTO, and engineers to turn that direction into a product. The product and marketing experiences I helped build supported Treasure's growth from $0 to $10M in assets under management.

Explore Treasure

Making a new workflow usable at JITX

At JITX, I worked with electrical engineers and software engineers to make circuit-board design through code approachable. My work covered the core product experience, activation, and acquisition: helping people understand the value, reach it, and build it into their daily work.

Explore JITX

Close to the technology. Closer to the customer.

I'm pursuing an M.S. in Computer Science at Georgia Tech, specializing in Machine Learning. I've built neural networks with NumPy and worked with Transformers, LSTMs, and CNNs in PyTorch.

I use that technical grounding to make better product decisions: what to test, where a model is likely to fail, and how to balance capability, cost, and trust. I build working prototypes with real data so customers can react to the actual experience and the team can learn before committing to a direction.

My career began in psychological research on software interventions for veterans with PTSD. That experience still shapes how I work. I want to understand the person, the context, and the consequences of getting a decision wrong.

Clear decisions. Shared ownership.

I make the customer problem, the business case, and the tradeoffs explicit. I want a team to understand why a priority matters, what we're choosing to leave out, and what evidence would change our minds.

After launch, I use product data and customer conversations to decide where to invest next. Adoption, customer value, and the economics of delivering it guide those decisions.

I also teach designers to build with code and AI through Technically Dangerous. Helping other people develop technical confidence is part of how I lead.

Away from the screen.

I meditate, grapple, and enjoy getting to know people deeply. Meditation helps with perspective. Grappling is a reliable reminder that a good plan still has to survive contact with reality.

I'm drawn to hard product problems where customer trust, technical depth, and business judgment all matter. If that sounds like your team, let's talk.