Privacy-enhancing technologies (PETs) have captured the imagination of cryptographers, engineers, libertarians, and protocol designers for over a decade. 

From zero-knowledge proofs (ZKPs) to fully homomorphic encryption (FHE), multi-party computation (MPC), and trusted execution environments (TEEs), these tools represent a leap forward in what’s technically possible.

But so far, that promise remains largely……..a promise. PETs have been architected, benchmarked, and demoed, but not widely adopted. Vitalik Buterin recently wrote a post on why privacy matters, emphasizing that it leads to more (1) freedom; (2) order; and (3) progress. We didn’t have the privacy technology back when crypto started. We do now.

While there are some technical aspects to Vitalik’s post, most of it is written to appeal to the web3 zeitgeist which seems to have lost its way, relegating zero knowledge technology to merely a scaling solution. 

In fairness, some of these are very good innovations. Miden has taken a very fresh approach to blockchain design based on the insight that if blockchains were to be designed from scratch, they would not look much like Ethereum or Bitcoin. Miden created the category of “edge computing,” taking full advantage of the feature of ZK technology that makes it a good scaling solution – it is computationally cheaper to verify a proof than run a full computation of the entire algorithm. For this reason, Miden pushes all heavy computation to the client side, and the onchain component is just proof verification. 

“What excites us most about Miden isn’t just that we’re optimizing how blockchains work, it’s that we’re fundamentally changing who they can work for. By pushing computation to the edge, we’re opening the door to compliant, private applications that were never possible before. This is how we make blockchain infrastructure viable for real-world institutions.” – Azeem Khan, Co-founder of Miden 

While the scaling solution seems to be the driving force behind the ZK trend, there is another aspect to ZK that is under discussed. At Myosin, in our discussions around ZK technology, near instant consensus emerged: that the privacy enhancing technology space has become nerd-sniped. 

This article isn’t a technical deep dive. Truthfully, there are more qualified folks out there who have covered that. 

Our focus is a shift in lens from “how PETs work” to what they can enable, moving the conversation from acronyms to adoption and highlighting real use cases where PETs can drive meaningful value and market fit. 

PETs are no longer an experimental technology waiting to breakthrough, they are here knocking on the door of mainstream adoption. This means more than just scaling blockchains and providing onchain privacy. This means taking the magic to the wider world. 

If you’re a tech-savvy executive at a large multinational corporation wondering if you missed the train on the emerging Web3 technology, you’re in luck. The best part is just getting started. 

The impact of PETs will soon be felt across the globe and across industries, from finance and banking, healthcare, data security, consumer applications, Internet of Things (IoT) based enterprises, supply chains, identity verification (including through biometrics), and many others. The total value that can be unlocked from this is in the order of billions of dollars. 

What PETs Actually Do

All PETs solve a version of the same problem: how to obtain the benefits of data (or sharing data) without exposing the data itself. Each PET addresses this in a different way. 

• ZKPs prove something is true without revealing anything else.

• FHE enables operations on encrypted data without decrypting it.

• MPC allows multiple parties to jointly compute a result without any one party .

• TEEs offer secure environments where computation is encrypted, not visible even to the TEE provider.

Each tool has trade-offs in terms of performance, complexity, and trust assumptions. But their shared utility is clear: they enable trust without exposure.

The next question is: trust for whom, and to what end?

Where PETs Unlock Adoption 

PETs can solve so many different problems, it is virtually impossible to fit all of it into one post. To get started, it is best to think of different categories of problems.

1. Solving Verification Dilemmas: No privacy considerations or temporary privacy considerations

Imagine a startup founder pitches an executive on a powerful algorithm, but won’t share the code. The executive wants to test it on proprietary data, but he can’t share that either. Millions are on the table, but so is the founder’s IP. Neither can verify the other’s claim without giving up what they’re trying to protect.

This is the classic verification dilemma, where trust breaks down because there’s no safe way to verify a claim without disclosure.

Privacy-enhancing technologies (PETs) can break the deadlock.

In fact, most of the efforts going into ZK today are focused on compressing algorithms. Risc-Zero’s product Boundless creates a marketplace for verifiable compute. In this marketplace, when a Prover submits a ZK proof they can include cycle counts in the metadata. which itself is made cryptographically secure i.e. can’t be altered without destroying the proof itself. A similar solution can be applied to any computer program including any allied metadata to resolve such dilemmas. 

Supply chains have verification problems too. Say you’re buying champagne that the seller claims is from Champagne, France. You scan a QR code that takes you to a website verifying this, but how do you know it’s not fake? ZK Proofs solve this with a proof tied to the product’s origin that can be verified independently of a single source.

It’s worth noting that using Zero Knowledge Proofs in supply chains is not a new topic. Chainlink has been contemplating this as a use case for years.  

In both cases it’s about proving just enough to make trust possible before disclosure.

2. Enabling Verification without Disclosure

Sometimes it’s not just about verifying a claim, it’s about not revealing anything at all.

Let’s revisit our founder and executive. This time, the founder isn’t selling. He wants to license his algorithm and charge a premium. The executive wants proof it works, but without seeing the code he won’t pay. The founder won’t accept deferred payments, he needs revenue on the books to survive. No one budges. The deal dies.

This is Arrow’s Information Paradox: to assess the value of information, you often have to reveal it which ends up destroying its value. It’s why trade secrets are hard to monetize, and why so many IP-rich businesses stall at the negotiation table.

This doesn’t just apply to startups and Intellectual Property. In Open Finance, insurers could offer better, cheaper and more tailored products if users shared more data, but privacy laws and fragmented systems make that impossible. PETs solve for trust without disclosure and that could unlock billions in GDP growth, especially in developing markets.

The opportunity here is massive: trust, at scale, without leaks.

Silence Labs is leading the charge when it comes to the adoption of Open Finance. Their advanced solutions combine MPC and ZK technology to achieve the aims of Open Finance while complying with privacy and data disclosure laws. Under the Open Banking regime, sharing of customer data between banks enabled banks to make more customised loans. Open Finance extends this concept to other financial products such as insurance. This is in large part possible due to the non-rivalrous nature of data – the ability of one piece of data to be resold multiple times and create additional value. Open Finance is projected to grow at a CAGR 22% and to reach a total market capitalization of USD 140.7 Billion over the next 8 years.  

3. Selective Disclosure: Identity

Most identity systems are broken in opposite ways.

• Web2 credentials leak too much: names, birthdates, financials are all on display, completely destroying anonymity and privacy.

• Web3 wallets leak too little: anyone can create infinite anonymous accounts, making systems like DAOs easy to game, completely destroying accountability.

The result? Web2 is surveillance by default. The current web3 system is fundamentally unaccountable. This is as true of Wallet addresses as it is of other solutions such as the Gitcoin Passport or Polygon ID. 

What we actually need is privacy and accountability, identity systems that reveal just enough to verify eligibility, without exposing everything else.

New solutions such as 0xKYC provide both accountability and privacy. 0xKYC also provides a verification against known and established Web3 frauds list as well as sanctions lists that are applicable in the real world. Web3 projects are adopting 0xKYC for ensuring fairness in giveaways, airdrops, ensuring fairness in gaming and other aspects.

Dock takes a different approach, catering to several well established Web2 entities, including biometrics companies, educational credentials, and shipping companies. Dock’s model is built on two core components: (1) verifiable, digitally secure credentials which are cryptographically secured representations of identity information that cannot be tampered; (2) ID wallets that provide users with control and flexibility over their identity information.  

The potential of decentralised identity is massive, affecting areas such as IAM management, reducing the need for multiple KYC, bureaucratic delays, and far superior compliance with regulations. Nethermind has also recognised the potential of usage of Zero Knowledge technology in identity solutions as a way to increase Sybill resistance.  

4. Selective Disclosure: Compliance and Governance

Disclosure laws are meant to protect the public – KYC for anti-terrorism, SEC filings for investor safety, ID checks for age restrictions. But in practice, these disclosures create new risks: leaks, misuse, and irreversible exposure.

In litigation, companies suing over trade secrets are often forced to re-disclose those same secrets in court, sometimes losing more in exposure than they stood to gain in damages. 

These are disclosure problems and the law solves them through less than ideal and often vulnerable compromises. PETs offer strong math based solutions that solve these problems perfectly. With PETs, a business can prove they meet regulatory requirements without revealing sensitive data using precision tools for compliance not blunt instruments of exposure. 

On the other hand, governments can demonstrate integrity in their operations, such as balance sheet stress tests for banks, without compromising operational confidentiality. Even subjective legal standards, like proving no collusion in antitrust cases, can be aided with cryptographic evidence, for example, with PET-based verification on private communication logs of key managerial personnel.

ZKPass is a protocol that employs MPC and zk proofs in order to streamline compliance across industries, centralised finance to healthcare. It ensures data privacy under GDPR, enables secure data sharing between hospitals, and supports privacy-preserving ad targeting.

5. New Business Models

Privacy is not just a feature, it can be a foundation for entirely new markets. If you’ve made it this far, you’ve probably picked up on a theme. There exist a variety of use cases for which the current solution is an imperfect legal or commercial one. 

Cryptography offers a path to making a product that solves any problem perfectly. Remember how we spoke about selective disclosures to aid with regulatory compliance? These business models take the logic one step further. 

Today’s imperfect solution typically assumes the guise of an intermediary auditing firm. This can be a law firm, a technical consultancy firm, or even one of the big four auditing firms. All of whom can be disrupted through a fully decentralised network leveraging wisdom of the crowds. 

With PETs, A decentralized network of lawyers can provide legal opinions, validated and refined through collective expertise, without ever knowing each other’s identities.

Prediction markets such as Polymarket are in fact an instance of the wisdom of the crowds principle. An added privacy layer could make the market even more accurate for the same reason that voting systems need privacy.

The same concept can be applied to any field – engineering, material sciences, anything that relies on “experts.”

In digital content, the Coalition of Content Provenance and Authenticity (C2PA) ensures digital authenticity, but current solutions rely on trust. With PETs, these can become cryptographically verifiable. A recent project at a hacker house conducted by Succinct, Celestia and others offered a way for content to remove the trust assumption and have every alteration of the image proven cryptographically, creating an immutable provenance chain.

These are not just applications of PETs. They are new categories that only exist because of PETs.

Why Privacy Tech Hasn’t Found PMF (yet)

If these use cases are so clear, why aren’t they live?

Three reasons stand out:

1. The talent is clustered at the infrastructure layer.

Most PET teams are protocol engineers optimizing proof systems, not product teams building UX around proofs. Don’t get us wrong. Some of the best builders working on this are doing important work. But they may just be missing the forest for the trees. 

2. Use cases require integration.

Many PET applications need coordination between multiple parties, industries, or jurisdictions. Adoption is gated by incentive alignment, not compute cycles. That’s why we are bullish on use cases that enable disclosure in ways that were not possible before.

3. No clear go-to-market model.
   Selling “privacy” isn’t enough. There is a section of Crypto Twitter that regularly puts out content focused on privacy, shilling it like a mantra even when most people don’t really care that much. The winning PET-native apps will solve an existing business problem, better and more trustlessly than incumbents.

What’s Next

We’re at an inflection point. PETs are (almost) technically mature. The infrastructure is ready. But adoption won’t come from more benchmarks or proofs of concept.

It will come from use cases that:

• Solve a painful, urgent problem for real world users, not just crypto bros;

• Build enjoyable UX around proofs, not just provers;

• Shift trust away from intermediaries and toward cryptographic verification.
  
  
  

PET-native apps will not win because they’re private. They’ll win because they’re better – faster, more secure, more composable, and more aligned with modern expectations of data ownership and coordination.

A Call to Builders

Privacy tech isn’t just a layer. It’s a whole new primitive.

If you're building PET infrastructure, the challenge now is use case development. If you're building products, the opportunity is to bake PETs into the core, not as a bolt-on, but as the backbone. Aztec Network embodies this philosophy.

Either way, the market won’t reward complexity for its own sake. It will reward usable trust. Don’t build a solution that then goes in search of a problem. 

The real PET revolution won’t be technical. It will be product-led. 

If you’re working on AI, identity, compliance, or coordination and think PETs could unlock a better user experience, let’s talk. We collaborate with founders to scope and launch PET-native products.