Privacy isn’t a luxury - it’s a necessity. 

Businesses need encryption to protect sensitive information and prevent exploitation, especially in Web3 where transactions remain publicly visible. DeFi trades can be front-run, AI models can be reverse-engineered, and sensitive business insights can be leaked. 

This is a key reason that institutions have yet to move on-chain, and solving it is important for the future of blockchain. And yet, without custom, easy-to-integrate privacy solutions, it is extremely hard for projects to operate on-chain without confidentiality.

That’s where Arcium comes in, operating as an ‘encrypted’ supercomputer that allows any project to incorporate encryption into its workflow.

Below, we’ll provide a simplified overview of why this matters to your business and how Arcium works on the back end. 

How Does This Work?

Arcium works by allowing multiple parties to work together in solving any type of problem while keeping individual inputs private.

Imagine a world-famous soft drink company (like Coca-Cola) that wants to keep its secret formula private while still mass-producing its drinks across the globe.

To make this work:

• Each supplier provides an ingredient: one supplies the vanilla, another refines the sugar, and another prepares the caramel. But no supplier knows the full recipe.
• The mixing process is compartmentalized: different teams manage carbonation, bottling, and quality control, but no single department sees the entire recipe.
• The final drink is produced: Enjoyed by millions worldwide yet the original formula remains a closely guarded secret.

With Arcium, the same can be applied to nearly any Web2 or Web3 business or application. For example:

• A financial institution could run privacy-preserving data analysis across a wider user base, improving their product offering.
• A DeFi protocol can execute private trades while preventing front-running.
• An AI company can train models on encrypted datasets without exposing proprietary data.

This is a big deal.

Why Data Privacy Matters

Imagine if everyone could see Coca-Cola’s recipe before the drink was bottled:

• Competitors could copy it and undercut it.
• Suppliers might manipulate ingredient pricing knowing how much Coca-Cola depends on them.
• Bad actors could tamper with the formula, ruining its consistency and quality.

In the real world, privacy isn’t a luxury—it’s essential. Many industry leaders agree that privacy is critical to Web3’s future, as it underpins the security and functionality of everything from healthcare and finance to AI, decentralized identity, and beyond. Without strong encryption, sensitive data becomes exposed, hindering secure AI training, compromising private trading strategies, and making it impossible to build advanced on-chain applications like dark pools.

But historically, maintaining privacy meant locking data away, limiting potential and innovation. With Arcium this changes, where data can remain private but still usable to its full extent. This becomes foundational not only for Web3 but also for governments, supply chains, communications, compliance tech, and countless other verticals that can unlock numerous possibilities without risk of exposure or exploitation of their sensitive data. This is the power of encrypted computation.

Understanding Encrypted Computation with Secret Recipes

Encrypted computation allows applications and organizations to process data in a fully encrypted state. This means data remains secure even when being used. There are several approaches to enabling private computation, each has its strengths and weaknesses. Sticking with our Coca-Cola example, here is a quick overview of the different approaches:

1. Fully Homomorphic Encryption (FHE): Imagine the Coca-Cola formula being made in a secure factory, where the drink is mixed and created without anyone ever seeing the ingredients. Extremely private, but slow and expensive.
2. Trusted Execution Environments (TEEs): A trusted bottling plant mixes the drink in a secure facility. But what if someone inside leaks the formula? Not truly secure.
3. Zero-Knowledge Proofs (ZKPs): Coca-Cola proves it has a secret formula without revealing what it is. Great in theory, but doesn't allow the different departments to coordinate privately.

The most effective approach is Multi-Party Computation (MPC), which works just like our earlier secret recipe analogy, allowing multiple teams to contribute ingredients and processes without ever revealing the full formula. 

We’ll break it down further below.

For more info on MPC, we also wrote a solid ELI5 MPC Overview here.

How Does Arcium enable Secret Recipes to be made?

Keeping with our secret recipe analogy, Arcium can be thought of as a high-tech factory for private data processing.

To bring this to life, Arcium has different components working together, including terms such as Arcis, MXEs, arxOS (Arx Nodes +Clusters), which we’ll explain using metaphors below.

Arcis is the development framework, where the secret recipe is defined. arxOS is Arcium’s execution engine that includes Arx Nodes, which are individual computers, functioning like specialized workers in a secret recipe production line. These Arx Nodes collaborate by executing “MXEs”, each handling a different part of the process without seeing the full formula, with the production taking place in Clusters (secure warehouses).

Here’s how this works:

• The Secret Recipe (Computation Definition with Arcis circuit): The blueprint for the drink, defining the exact ingredients, proportions, and preparation process, so that the team follows a unified standard.
• The Department (MXE): The organizational division within the Coca-Cola Company that’s dedicated to assembling the specific Coca-Cola drink. 
• Process Specialists (Arx Nodes): Individual employees handling specific responsibilities, such as extracting the vanilla, refining the sugar, preparing the caramel, etc.
• The Warehouse (Cluster): The physical location consisting of many Process Specialists (Arx Nodes) who operate inside the Department (MXE)  ensuring that the formula remains confidential even as it’s processed.
• The Final Product (Computation Result): A bottle of Coca-Cola enjoyed by millions, but no employee or supplier outside the core company knows exactly how it was made.

Businesses, retailers, and consumers who receive and use the final product (computation result) would be referred to as Computation Customers, referring to those who order the final product. In reality, this is likely an AI project, DeFi project, and so on that wishes to perform encrypted operations.

Why This Approach is Game-Changing

By using this approach, Arcium solves major encryption challenges:

• Scalability: Just as Coca-Cola mass-produces its drink while keeping the recipe secret, Arcium can handle massive computations while protecting data privacy.
• Customizability: The recipe (MXE) can be adjusted for different needs. Want higher security? Faster performance? Lower costs? Arcium adapts to your workflow.
• Interoperability: Just like Coca-Cola is bottled in multiple countries, Arcium integrates seamlessly across Web2 and Web3 systems.

What does this mean in practice?

Nearly every industry has valuable data worth protecting, and Arcium provides a highly flexible solution for a wide range of use cases such as:

For DeFi projects, that might be sensitive transaction data or proprietary trading algorithms. For example, DeFi projects can use Arcium to create dark pools, which account for ~40% of daily U.S. trading volume. 

For AI projects, that might be proprietary models, training datasets, or inference requests. Companies can use Arcium to train and run AI models on encrypted data, allowing multiple parties to collaborate on machine learning without exposing sensitive information or risking data leaks.

For a DePIN project, that might be infrastructure data or user analytics. These projects can use Arcium to securely process data from decentralized networks (like sensor grids or storage systems) without exposing sensitive details.

For institutions, that might be confidential transactions or client data, but use cases can extend far beyond this, such as performing collaborative data analysis with other organizations while keeping sensitive information private and compliant with regulations like GDPR.

Organizations can even opt to run some (or all) of the operations using their own in-house Nodes, giving them flexibility over how much control they exert over operations. These would be set up as “permissioned clusters”.

We firmly believe that nearly any project can benefit from a flexible MPC solution like Arcium.

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