What 230 Hours of Customer Discovery Taught Us About Privacy Demand

We’ve spent 230+ hours talking to Web3 teams trying to figure out one thing: who actually needs privacy, and in which form we should deliver it.

Here’s what we learned and what it means for builders who want to make privacy useful, not theoretical.

The Uncomfortable Truth About Privacy Demand

After six months of intensive user research, one pattern became crystal clear:

Institutional privacy has a clearer ROI than consumer privacy- yet it’s not limited to institutions. High-stakes users with public reputations actively seek it, and even retail users signal the same through their habits: splitting activity across wallets, withdrawing through intermediaries, and deliberately avoiding linkability.

This isn’t what we expected to find when we started Fhenix. Like many privacy advocates, we assumed individual users would drive demand for confidential computation. The reality is more nuanced.

Institutions, whether they’re DeFi protocols managing MEV, gaming companies protecting game economies, or DAOs conducting sensitive governance can immediately quantify the value of privacy.

A DeFi protocol can calculate exactly how much they lose to frontrunning.

A prediction market can measure the premium users pay for sealed bids.

The math is straightforward.

Consumer privacy, while critically important, operates differently. Users often don’t realize they need privacy until they’ve been burned — and when they do, they expect it to “just work” without friction or complexity.

So Why Are We Building for Everyone?

If institutional demand is clearer, why not focus exclusively on enterprise use cases?

Privacy tech is still nascent, even Fully Homomorphic Encryption (FHE), which we believe is the endgame cryptographic primitive, needs extensive real-world testing.

Mainstream DeFi users help us validate two critical things:

1. Tech stack capabilities:  Can our FHE implementation handle transaction volumes, gas costs, and UX demands of real applications?
2. Product–market fit: Are we building the right abstractions and dev tools for privacy to become as common as smart contracts?

That’s why we’re exploring multiple use cases simultaneously. Every encrypted AMM swap, confidential voting mechanism, and private on-chain game teaches us where the technology breaks and where it shines.

Recent Experiments in Privacy UX

Encrypted Uniswap V4 Hooks

→ Confidential liquidity pools where trading activity stays private until settlement. Tests whether FHE can support AMM logic while preserving composability.

Fhenix402

→ Our take on private x402 payments, enabled by FHE. Read this deep-dive article to see how a one-day experiment revealed the missing piece of Web3's privacy infrastructure.

Redact

→ A privacy-preserving social protocol letting users control what they reveal and to whom. A sandbox for confidential identity and reputation.

Each experiment validates a different layer of our infrastructure. Some will find product–market fit. Others will teach us what to fix next.

The Real Lesson: Privacy Needs a Vocabulary

After 230 hours of conversations, one thing is obvious:

the privacy space lacks a shared language.

When someone asks “do you need privacy?”, the answer depends entirely on:

• What type: confidentiality, anonymity, unlinkability
• Against whom: users, operators, validators, governments
• At what cost: performance, gas, UX
• With what guarantees: cryptographic, hardware-based, or economic

We’re building a privacy stages framework: something as legible as L2beat’s Rollup Stages, but for confidential computation.

Until builders have that clarity, we’ll keep solving mismatched problems.

What This Means for Privacy Builders

If you’re building in privacy, here’s what we’ve learned:

• Start with value. Don’t say “privacy matters.” Say “here’s what you lose without it — and what you gain with it.”
• Target the extremes. Focus first on high-stakes use cases: large financial transactions, governance, competitive games.
• Design for evolution. Privacy infra shifts fast. TEEs proved the concept, but FHE and ZK are rapidly becoming practical.
• Ship in public. Only real users and transactions expose what theory can’t.

Closing Thoughts

The journey toward mainstream privacy is just beginning. But after hundreds of hours of discovery, we’re confident we’re asking the right questions, even if the answers keep evolving.

In the process, a few areas keep emerging as the highest-impact frontiers: private payments and stablecoin rails, privacy-preserving intent execution for agents and institutional compliance.

These emerging “impact zones” are shaping our next episode, where we dive into each lens in detail.

This is Episode 1 of Privacy PMF Stories where we share what we’re learning about building privacy tech that people actually use.

👉 Want to build with us? Explore our developer docs or join Telegram to start experimenting with FHE on Ethereum.

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