Introduction
The Trust Problem in Finance
Modern finance runs on trust. When a bank says it holds $10 billion in reserves, you trust the bank. When an auditor confirms those numbers, you trust the auditor. When a protocol claims it's fully collateralized, you trust the protocol's dashboard.
But trust breaks. Banks fail. Auditors miss things. Dashboards can show whatever the operator wants them to show. History is full of examples from traditional finance collapses to crypto platform failures, where the numbers on the screen didn't match reality.
The question isn't whether institutions are honest. Most are. The question is: why should you have to trust at all when technology can provide proof?
A New Approach: Verifiable Proof
This system replaces trust with verification. Instead of asking "do I trust this entity to report honestly?", it enables anyone to ask "can I verify this myself?"
Every piece of financial data that enters the system goes through a pipeline that produces cryptographic proof which is a mathematical evidence that:
The data was processed by legitimate, untampered software
The computations (like summing reserves) were done correctly
No one, not even the system operator could have modified the results
The numbers haven't been changed since they were produced
This isn't a new idea. Blockchains do something similar for transactions. But this system brings the same level of verifiability to off-chain financial data — the real-world numbers that most of DeFi and traditional finance actually depend on.
Who Is This For?
This documentation is for anyone who wants to understand how the system works and why it's secure. You don't need to be a cryptographer or a developer.
Protocol users who want to know their funds are actually backed
Institutional partners evaluating the security model
Regulators and auditors who need to understand the verification process
Developers building integrations (the technical details are in the codebase)
What You'll Learn
This documentation is organized into sections that build on each other:
The complete journey from raw data to verifiable proof
How secure hardware guarantees computation integrity
How math proves correctness without exposing private data
How data is fingerprinted, organized, and linked over time
How anyone can independently check a proof
The full picture of what's protected and how
You can read them in order for the full picture, or jump to any section that interests you.
The Core Idea in 30 Seconds
Private financial data goes into a secure hardware enclave — a sealed environment that no one, not even the server operator, can peek into. Inside that enclave, the data is processed, committed, and proven correct using zero-knowledge proofs. The hardware itself signs everything, producing an attestation that traces back to a trusted certificate authority. The result is a single proof payload that anyone can verify independently, without needing to see the original data.
Two independent guarantees back every proof:
Hardware says it's real — the secure enclave's signature proves the computation happened in genuine, untampered hardware
Math says it's correct — zero-knowledge proofs provide mathematical certainty that the computations are right
An attacker would need to break both simultaneously — the hardware and the mathematics — which are completely independent systems.
How This Is Different
Most systems in this space rely on one of these approaches:
Trusted oracles
You trust the oracle operator
Multi-sig attestation
You trust the signers
Periodic audits
Snapshots in time, not continuous
On-chain computation only
Limited to data already on-chain
This system combines hardware attestation and zero-knowledge proofs to create continuous, real-time verification of off-chain data without trusting any single party. The proof speaks for itself.
A Note on Terminology
Throughout this documentation, you'll encounter some terms that might be unfamiliar:
Attestation — a signed statement from hardware proving what code ran and what it computed
Commitment — a cryptographic fingerprint of a value that hides it but can be verified later
Merkle tree — a data structure that combines many fingerprints into a single root hash
Zero-knowledge proof — a mathematical proof that something is true without revealing the underlying data
Enclave — an isolated, tamper-proof execution environment within a processor
Collateralization — whether reserves are sufficient to cover liabilities
Don't worry if these don't fully click yet. Each section explains the relevant concepts in detail with analogies and diagrams.
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