Why We Were Early Investors in Zama

By Harrison Dahme and Alex Botte, Partners at Hack VC

Some ideas take time to become obvious. Confidentiality in blockchains is one of them. For years, the industry treated radical transparency as a feature rather than a tradeoff. Previous administrations also enforced this view. In practice however, that assumption has quietly capped adoption and limited institutional design space. Financial systems, enterprises, governments, and even most individuals do not want their most sensitive data broadcast to the world.

We invested in Zama because we believe confidentiality is foundational, and not just a niche improvement to blockchains.

We made our initial investment more than one year ago, deep in the era when privacy was considered forbidden, and well before “confidential compute” became fashionable again. What convinced us then still holds today - Zama is building the most credible path to confidential, programmable, and verifiable applications on public blockchains.

Transparency Was Never the End State

Public blockchains solved an important problem. They made it possible to verify computation without trusting an intermediary. That breakthrough unlocked permissionless finance, composable software, and a new way to coordinate economic activity.

But it also introduced a structural flaw.

Everything on-chain is public because validators need to see the data to verify state transitions. Balances, transfers, bids, positions, identities, and governance votes are all exposed by default. For hobbyists, this can be acceptable. For enterprises, institutions, and most real economic activity, it is not.

The result is a paradox:

• We want public verifiability
• We also need confidentiality
• Historically, we have been forced to choose one or the other

Private chains give confidentiality but sacrifice composability and trust minimization. There are several forms of private tech today that we outlined in this 2024 research article. Here’s a quick summary:

• Zero-knowledge (ZK) proofs - these help, but are often application-specific and difficult to generalize. They’re more suited to verifying the output of a process without revealing the inputs.
• MPC - powerful, but introduces coordination and latency constraints at scale
• TEEs - trade cryptographic guarantees for hardware trust assumptions. While an excellent solution, it also introduces hardware dependencies, which aren’t appropriate for all use cases.

Fully Homomorphic Encryption (FHE) changes the equation. It allows computation on encrypted data without ever decrypting it. In principle, this enables confidentiality and verifiability at the same time. For decades, FHE was too slow and too impractical to matter, but that has now changed.

We believe Zama is the world leader in FHE, and poised to push the technology past the inflection point. To date, they have been uniquely capable of moving FHE from theory to production.

What Is Zama

Zama is building a confidentiality layer for blockchains powered by FHE.

Rather than launching a new L1 or L2, Zama sits on top of existing chains. Developers deploy standard contracts on Ethereum, other EVM chains, and eventually Solana. Sensitive data stays encrypted at all times, including during execution.

At a high level, Zama enables:

• Confidential smart contracts on public blockchains
• End-to-end encryption of state and inputs, even during processing
• Public verifiability of encrypted computation
• Programmable rules for who can decrypt what

Importantly, Zama does this without forcing developers to learn new programming languages or cryptography. If you can write Solidity or Python, you can build confidential applications.

How It Works

Zama combines several techniques into a coherent system, each used where it is strongest.

FHE as the core privacy tech: FHE allows computation directly over encrypted data. Validators and coprocessors never see plaintext, but anyone can verify that the computation was performed correctly and confidentially.

Coprocessors for scale: Running FHE directly inside the EVM would be prohibitively expensive. Zama offloads heavy computation to coprocessors. The base chain remains fast, while FHE operations are parallelized and scalable.

MPC for key management: Decryption keys are split across multiple parties using threshold MPC. No single operator can decrypt data unilaterally.

ZK proofs for control: ZK proofs are used narrowly to ensure inputs are correctly encrypted. This keeps costs low while preserving security.

The result is a system that is:

• Verifiable, because anyone can recompute encrypted operations
• Composable, because confidential contracts can interact with each other and with non-confidential ones
• Scalable, because FHE computation is parallelized and hardware-accelerated over time

Developers simply mark which variables should be private. Access control is defined directly in the smart contract. Compliance logic becomes code.

Why We Invested Early

When we underwrote Zama over a year ago, several things stood out.

1. Zama is effectively a platform bet on FHE

FHE is a foundational capability. If it works, it becomes a horizontal primitive across finance, identity, governance, AI, and enterprise software. Zama is the company building the core libraries, tooling, protocols, and developer ecosystem around FHE. In our internal discussions, we described it as closer to an index on the entire FHE space than a point solution.

2. The team is world class

FHE is notoriously difficult. It sits at the intersection of cryptography, distributed systems, hardware, and compilers. Zama’s team includes pioneers of homomorphic encryption, applied cryptographers, and engineers who have shipped real systems at scale.

3. Performance was crossing the threshold

The primary historical risk in FHE has always been performance. Zama had already demonstrated massive gains by the time we invested. Since then, they have continued to improve throughput by orders of magnitude. Today, Zama can already process encrypted transactions at speeds that cover the vast majority of on-chain use cases.

4. The use cases are real and expanding

Confidentiality unlocks concrete applications:

• Confidential stablecoin payments with embedded compliance
• Tokenization of real-world assets on public chains
• DeFi without front-running or balance exposure
• Sealed-bid auctions and private distributions
• On-chain identity and governance without coercion

5. Timing risk was the right risk

Every transformative technology looks early until it is suddenly inevitable. We debated whether FHE adoption might still be a few years ahead of the market. In the end, we preferred that risk to the alternative. Being late to a foundational layer is usually far more expensive than being early.

Where This Goes

We believe confidentiality will follow a similar arc to encryption on the internet.

First, it is optional. Then, it becomes expected. Eventually, it is invisible and default.

Zama’s vision is programmable confidentiality as a core property of decentralized systems. That is a much bigger idea. It enables public infrastructure that respects privacy without sacrificing verification.

In our view, that is a necessary condition for blockchains and beyond to support:

• Global payments
• Institutional finance
• Enterprise workflows
• Digital identity
• Governance at scale

Post Script: Our “Beyond Blockchain” Thesis

While our thesis centers on blockchain confidentiality, FHE is a horizontal primitive with implications far beyond crypto. We see Zama's technology as a foundational layer for any system that requires computation on sensitive data without exposing it. Here are a few examples:

AI and Machine Learning

This may be the most consequential near-term expansion. As AI systems become more capable, the trust problem intensifies:

• Inference on private data - Users increasingly want to query powerful models without revealing sensitive inputs (medical records, financial data, proprietary business information). FHE enables encrypted inference where neither the model provider nor intermediaries see the plaintext. Zama is already working towards this with their Concrete ML library which displays impressive performance.
• Confidential training - Organizations can contribute to training datasets without exposing underlying data, unlocking collaborative AI development across competitors and regulated industries.
• Agent-to-agent confidentiality - Increasingly, and with the release of Claude Cowork, we live in a multi-agent world. Autonomous AI agents transacting on behalf of users will need to protect sensitive parameters and intentions, particularly in adversarial environments.

Healthcare and Life Sciences

• Patient data can be analyzed across institutions without leaving encrypted form
• Drug discovery collaboration without IP exposure

Financial Services (Off-Chain)

• Cross-institutional fraud detection without sharing customer data
• Confidential credit scoring and underwriting
• Regulatory reporting that proves compliance without exposing positions

Enterprise and Government

• Secure multi-party analytics across supply chains
• Confidential bidding and procurement
• Intelligence sharing between agencies without full disclosure

The Common Thread

Each of these domains shares the same paradox we identified in blockchains: the need to compute on data while keeping it confidential. FHE is the only cryptographic approach that solves this without hardware trust assumptions, coordination overhead, or application-specific constraints.

Zama's position as the infrastructure layer - not the application builder - means they capture value across all of these verticals as FHE adoption expands.

Disclosures

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