Key Concepts

To understand how the system was redesigned to verify large datasets efficiently, the following concepts are referenced throughout this case study:

• Merkle Tree: A data structure that allows large datasets to be verified efficiently by storing a single cryptographic summary of the data. Individual entries can be validated without storing or processing the full dataset on-chain.
• Smart Contract: A program deployed on a blockchain that executes predefined rules automatically. Smart contracts are transparent and secure, but are constrained by execution costs and storage limits.
• On-Chain Storage: Data stored directly on the blockchain. While secure and tamper-resistant, on-chain storage is expensive and impractical for large datasets.

Business Problem

A platform relied on a smart contract that managed access via whitelists. However, the architecture allowed for only one active whitelist at a time, with a strict limit of 1,000 entries. This forced all verified data into a single, constrained list, creating an immediate technical ceiling.

As usage grew, this design presented three critical business obstacles:

• Operational Friction: Initialising or updating a whitelist required dozens of sequential on-chain transactions. This process was slow, operationally heavy, and increasingly expensive during periods of network congestion.
• Prohibitive Storage Costs: Because the system stored every entry directly on-chain, rent costs increased linearly with the dataset. This made the business model unsustainable as the whitelist expanded.
• Strategic Stagnation: The client was unable to support larger enterprise partners or high-volume use cases, effectively stalling the product's roadmap and market expansion.

These combined limitations placed a hard ceiling on the product's scalability, preventing the business from growing alongside market demand.

Our Solution

We re-engineered the verification process by implementing a Merkle Tree structure, shifting the heavy lifting away from the expensive blockchain and onto an optimised off-chain system.

• Capacity Increase: Instead of storing individual entries on the blockchain, we stored a single Merkle Root. This allowed the system to securely verify up to 1,000,000 entries while using less blockchain space than the original setup.
• Transaction Compression: We reduced the setup process from 50 transactions down to just one. By only needing to publish the Merkle Root once, we eliminated 98% of the initial operational effort and cost.
• Cost-Optimised Verification: We shifted the data storage off-chain while maintaining on-chain security levels. Users now provide a small Merkle Proof to the contract, which validates their entry instantly and at a fraction of the previous cost.

This redesign transformed a tightly constrained contract into a scalable verification system suitable for real-world usage.

Results

A scalable, cost-efficient verification system capable of supporting large datasets on-chain.

• 1,000x Scalability: Expanded verification capacity from 1,000 to 1,000,000 entries, removing the primary barrier to business growth.
• 98% Reduction in Setup Effort: Streamlined the deployment process from 50 transactions to a single, efficient update.
• Cost Savings: Minimising on-chain storage significantly lowered transaction fees and rent costs.
• Market Expansion: With the technical ceiling removed, the client successfully pivoted to larger datasets, allowing them to attract enterprise-level customers for the first time.

The platform now supports large-scale verification reliably, removing the technical and cost barriers that previously limited growth.