Introduction: Precision as a Systems Property

INTMAX is redefining what mathematical precision means in the context of blockchain-based payments. By deploying a stateless architecture underpinned by zero-knowledge proofs (ZKPs), INTMAX achieves sublinear state growth, ultra-low data availability costs, and cryptographic auditability. This article explores INTMAX’s base rollup architecture, situating it within broader L2 design paradigms, and assesses its technical superiority in achieving scalable, secure, and private payment infrastructure.

Mathematical precision is about determinism, verifiability, and bounded computation. In payment systems, this means consistent transaction execution, minimized latency, and predictable throughput across adversarial environments. Where traditional L2 rollups trade state growth for scalability, INTMAX minimizes both without compromising on security or user privacy.

Stateless Architecture: Sublinear State Growth and Client-Side Computation

INTMAX is the first stateless zkRollup to achieve sublinear state growth, a significant milestone in blockchain scalability. Traditional rollups retain global state updates on-chain, leading to state bloat, validator centralization, and increased verification costs. INTMAX avoids this by pushing both state preservation and proof generation to the client-side. Users store their own state, and aggregators merely commit inclusion proofs and aggregate signatures.

Formally, INTMAX defines blocks as one of three types: deposits, transfers, or withdrawals. These are encoded in Lean as:

inductive Block (K₁ K₂ : Type) (C Sigma : Type) (V : Type) [PreWithZero V] where

| deposit (recipient : K₂) (amount : V₊)

| transfer (aggregator : K₁) (extradata : ExtraDataT)

(commitment : C) (senders : List K₂)

(sigma : Sigma)

| withdrawal (withdrawals : K₁ → V₊)

Here, V₊ ensures values are non-negative by construction. By pushing this logic into type-level constraints, INTMAX guarantees that every block operation respects value bounds without requiring runtime checks.

This block architecture underlies the formal guarantee that state updates scale as , rather than linearly with user count, due to Merkle-based commitments and authenticated dictionaries.

Every INTMAX transaction commits only 4–5 bytes of data to Ethereum L1, which is orders of magnitude lower than other zkRollups like zkSync or StarkNet. By keeping the global state off-chain, INTMAX reduces not just memory overhead but also the computational burden on validators, or in this case, users.

Zero-Knowledge Proofs and Proof Aggregation

The base rollup architecture of INTMAX utilizes recursive ZKPs for inclusion proofs and transparent ZKPs for commitment validation. The cryptographic pipeline is designed to ensure minimal on-chain footprint with maximum verifiability. To understand how INTMAX achieves this balance of minimalism and integrity, it’s essential to examine the distinct types of zero-knowledge proofs it employs, each contributing a critical function in ensuring both privacy and efficiency at scale.

zk-SNARKs validate transaction origin without disclosing sender identity or balances. These succinct proofs enable verification of complex computations without revealing any underlying data, preserving user confidentiality in every transaction. Recursive ZKPs, on the other hand, allow one ZKP to attest to the validity of multiple other ZKPs within a single Merkle root. This hierarchical structuring of proofs reduces verification time and supports scalability without increasing on-chain data. Finally, Transparent ZKPs generate cryptographic criterion, leveraging public randomness thereby removing the requirement for trusted setup ceremonies. This approach enhances the decentralization and auditability of protocols, aligning with the broader ethos of trustless systems. These proof systems provide a modular architecture that disseminates client-side data responsibility and trust assumption while enabling performance without centralized points of failure.

To ensure proofs map consistently to transaction behavior, INTMAX defines transaction validity as a dependent type:

abbrev Τ’ (K₁ K₂ V : Type) [PreWithZero V] := Kbar K₁ K₂ × Kbar K₁ K₂ × Option V₊

def isValid (τ : Τ’) := sender ≠ recipient ∧ (sender = Source → value.isSome)

abbrev Τ (K₁ K₂ V : Type) := { τ : Τ’ K₁ K₂ V // τ.isValid }

INTMAX constructs such a modular system employing each proof type to reinforce the others, equipping privacy and scalability, and operational decentralization. This modular proof system allows for parallel proof generation and aggregation, which ensures that invalid transactions are unrepresentable, enforcing correct behavior by design. Unlike other rollups that rely on a single sequencer or prover, INTMAX distributes proof responsibility across decentralized aggregators.

Aggregator Model and Privacy Mining

Aggregators in INTMAX are not elected and do not require staking. They are permissionless actors who post commitments and zero-knowledge proofs to the Ethereum mainnet. INTMAX reduces the risk of Maximum Extractable Value (MEV) exploitation, where sequencers front-run transactions for profit, by removing the need for centralized sequencers at all, mitigating transaction censorship. These risks are common in systems with centralized sequencing, and threaten both the fairness and neutrality of blockchain infrastructure. INTMAX’s design counters this by distributing proof responsibilities across a decentralized set of participants, making manipulation economically infeasible and procedurally difficult.

To guarantee those commitments, INTMAX uses an authenticated dictionary scheme with the following formal properties:

class ADScheme (K : Type) (M : Type) (C Pi : Type) where

Commit : Dict K M → CommitT C K Pi

Verify : Pi → K → M → C → Bool

binding : ComputationallyInfeasible <|

∃ (c : C) (k : K) (m₁ m₂ : M) (π₁ π₂ : Pi),

Verify π₁ k m₁ c = true ∧ Verify π₂ k m₂ c = true ∧ m₁ ≠ m₂

INTMAX also introduces a novel mechanism called “privacy mining.” Here, users deposit ETH into the system, which is cryptographically anonymized, and receive ITX tokens in return. These deposits populate the protocol’s Anonymity Set — a pool of indistinguishable user transactions that serves as a protective veil for individual metadata. A larger Anonymity Set increases the difficulty for adversaries to link transaction inputs and outputs, thereby strengthening resistance to correlation and deanonymization attacks. This structure not only preserves privacy but also reinforces protocol integrity without relying on punitive slashing or hierarchical validator elections.

Base Rollup vs. Optimistic and Standard zkRollups

In optimistic rollups like Arbitrum, state transitions are assumed valid unless challenged. This model introduces latency (challenge periods) and relies on fraud proofs. Standard zkRollups like zkSync prioritize validity proofs but still rely on global state updates.

INTMAX diverges from both optimistic and standard zkRollup designs by architecting a system that requires no fraud windows, commits a constant-sized data footprint regardless of user count, and enables universal composability without the need for bridges or external relays. By eliminating fraud windows, INTMAX avoids latency and the uncertainty introduced by challenge periods. Its constant-sized data model ensures that transaction costs and verification workloads remain stable as the network scales. Furthermore, its composable architecture allows seamless interoperability between applications and chains, enhancing developer flexibility and reducing attack surfaces typically introduced by interchain communication layers.

This base rollup design maximally reuses Ethereum’s L1 security without duplicating state or delegating control to centralized actors. By anchoring trust in Ethereum’s consensus layer, INTMAX avoids reinventing core infrastructure and instead focuses on optimizing throughput and privacy. Its integration of Ethereum-native sequencing preserves decentralization and composability, allowing applications to operate across layers without complex coordination protocols or intermediary trust assumptions. This design not only strengthens systemic coherence but also aligns with Ethereum’s broader roadmap toward modular, scalable execution.

The Data Availability Breakthrough

A critical constraint in rollup scalability is Data Availability (DA). DA is the guarantee that all data necessary to verify a transaction is actually accessible when needed. In most rollups, this is achieved by posting full transaction calldata directly to Ethereum’s L1, which ensures verifiability but bloats block space and incurs high fees. This trade-off creates a bottleneck for scalability, as the cost of maintaining availability grows with every additional user and transaction.

INTMAX sidesteps this constraint through a client-side DA model paired with verifiable computation. Instead of posting transaction data on-chain, INTMAX users retain their own data and generate zero-knowledge proofs that confirm data possession and transaction validity. Only compact cryptographic commitments, approximately 4–5 bytes, are posted to L1. This radically reduces the on-chain data footprint without compromising the ability to verify transactions.

The math behind this approach guarantees that the total DA cost grows as 0(log n) not 0(n), thanks to recursive verification and batch aggregation. Nethermind formally verified INTMAX’s core protocol logic in Lean:

theorem secure : ¬ adversaryWon (attackGame requests)

This theorem states that it is provably impossible for an adversary to drain funds or compromise balance integrity unless they can break their hash collision resistance or ADS binding, both of which are considered to be computationally infeasible.

As Justin Drake noted, INTMAX delivers “better-than-expected” DA performance. Because the system relies on recursive proofs and off-chain data integrity, DA costs grow logarithmically rather than linearly with network size. This approach not only enhances scalability but also shifts the locus of responsibility toward users, empowering them to manage their own data while maintaining the system’s trustless guarantees.

Formal Validation and Industry Endorsements

INTMAX has undergone independent validation by researchers at Nethermind, one of the most respected Ethereum research and development firms. Their formal analysis, published in March 2024, affirmed the protocol’s cryptographic integrity and verified key security properties of the system’s stateless rollup design. The review examined INTMAX’s use of zero-knowledge proofs, its data minimization architecture, and its privacy-preserving mechanisms, confirming that the protocol meets rigorous standards for proof soundness, state consistency, and adversarial robustness.

Among the highlights of the Nethermind report were INTMAX’s sublinear state growth, the correctness and integrity of its aggregated ZKPs, and the viability of its privacy model under real-world adversarial conditions. Importantly, the report also confirmed that INTMAX’s statelessness does not introduce new attack vectors, and that its reliance on client-side computation and decentralized aggregation preserves both scalability and decentralization.

INTMAX is therefore a performance system that withstands formal scrutiny, a unique category among L2 solutions. This aligns with earlier endorsements from Ethereum co-founder Vitalik Buterin, who praised INTMAX for delivering “a high level of scalability and privacy.” Together, these validations position INTMAX as a research-aligned protocol that pushes the boundaries of what L2 architecture can achieve.

Use Case Alignment: Why Payments?

In financial contexts, transaction metadata can expose competitive business strategies, personal spending habits, or politically sensitive affiliations. As a result, privacy is not optional; it’s foundational. At the same time, the volume of global financial transactions requires a protocol that can process thousands, even millions, of transactions per second without degrading performance or increasing cost.

Most existing Layer 2 solutions address only fragments of this challenge. Optimistic rollups like Optimism scale well by assuming transaction validity and relying on fraud proofs, but they expose transaction metadata and introduce latency through challenge windows. zkSync, a leading zkRollup, offers enhanced privacy through zero-knowledge proofs but still requires maintaining global state on-chain, limiting scalability and increasing storage costs.

INTMAX, by contrast, is architected for the full stack of payment requirements. It offers transaction privacy through client-side zero-knowledge proofs and scales horizontally by eliminating state growth entirely. Its stateless design, combined with near-zero DA overhead, enables efficient, high-frequency financial interactions without compromising on security or decentralization. This makes INTMAX uniquely suited for applications such as micropayments, business-to-business remittances, decentralized payroll, and real-time transaction settlement at internet scale. Whether the transaction is one cent or one million dollars, INTMAX handles it with cryptographic precision and structural integrity.

Risks and Limitations

As of this writing, INTMAX remains in its testnet phase, with a mainnet launch anticipated in the near future. While the protocol’s design is mathematically sound and formally validated, its operational resilience under real-world conditions has yet to be fully tested. This distinction between theoretical robustness and practical performance is critical, especially for a system intended to handle the rigors of high-frequency financial transactions.

One area of open inquiry is aggregator liveness in adversarial conditions. Because INTMAX uses decentralized, non-elected aggregators to post commitments and proofs, it’s essential to ensure that enough honest aggregators are available to keep the system running efficiently. Network incentives must align with sustained participation, particularly during periods of high volatility or low liquidity.

Another concern involves the user experience of managing client-side state. In a stateless system, users are responsible for holding and safeguarding their own transaction data and state proofs. While this model enhances decentralization and privacy, it also raises usability questions: What happens if a user loses their state data? Can mobile wallets adequately support this model without degrading performance or security? These are crucial implementation-level challenges that will shape adoption.

Lastly, privacy mining, while innovative, raises regulatory questions across jurisdictions. By design, it anonymizes ETH deposits and redistributes rewards in ITX tokens. But depending on the legal framework, this could trigger compliance issues related to Anti-Money Laundering (AML), Know Your Customer (KYC), or data protection laws. Clear guidance and careful jurisdictional analysis will be needed to ensure that the protocol remains compliant without compromising its core principles.

None of these concerns undermine the architecture itself. They are engineering and governance challenges which are solvable with community input, iteration, and rigorous testing. The protocol is structurally sound. What remains is the work of maturing it into a production-grade system.

Conclusion: Engineering Integrity by Design

INTMAX doesn’t just optimize for throughput or reduce costs, it represents a categorical shift in how we think about blockchain infrastructure for payments. Where other protocols specialize in singular virtues such as speed, privacy, or decentralization, INTMAX integrates all of these into a cohesive system that functions not in spite of its complexity, but because of its architectural clarity. By beginning from first principles and treating statelessness not as a compromise but as a foundational asset, INTMAX constructs a protocol that is lean, powerful, and resistant to the pitfalls that have plagued previous scalability attempts.

Its ability to maintain near-zero state growth, support verifiable computation with minimal on-chain data, and preserve user anonymity without sacrificing auditability places it in a class of its own. These aren’t just optimizations; they are the result of a systems-level commitment to mathematical, architectural, and ethical precision.

In doing so, INTMAX offers not only a technical roadmap but a philosophical framework for what payments could become: frictionless, borderless, and incorruptible. It envisions a financial infrastructure where freedom, privacy, and efficiency are not trade-offs to be managed, but core invariants to be preserved. If INTMAX succeeds in transitioning from testnet to production with its design intact, it won’t just improve payments. It will redefine what blockchain infrastructure can aspire to be.

References

• INTMAX Official Blog: https://intmax.io/blog

• Nethermind Validation Report: https://medium.com/intmax

• No State, No Trace: https://medium.com/intmax/no-state-no-trace-stateless-systems-and-the-future-of-digital-privacy-dc7681b2fcb5

• Vitalik Buterin, “Exploring L2 Designs”: https://vitalik.eth.limo

• Justin Drake, ETH Research Forum: https://ethresear.ch

• A Simple Stateless Blockchain Protocol: https://eprint.iacr.org/2023/1082.pdfWhy INTMAX Is the Most Mathematically Precise Payment Solution in the Industry: A Deep Dive into Its Base Rollup Architecture