Large language models are not inherently ill-suited for onchain use cases — in fact, there are many crypto products out there that have been majority built with LLMs. However, problems start to emerge when LLMs are only given access to work with onchain data at the blockchain level. Rather than
The stablecoin market is no longer a companion to the crypto market, it’s a major player moving significant amounts of money. According to Allium’s recent stablecoin report, total circulating supply of the stablecoin market reached $266.3 billion as of February 2026. That’s more than the GDP
Crypto builders rarely set out to learn accounting mechanics. But as soon as you try to ship analytics, financial reporting, risk monitoring, or compliance tooling, you run into a familiar problem: data that doesn’t reconcile. Balances don’t match transaction histories, aggregates drift over time, reorgs silently corrupt mechanics.
ERC-8004 is a standard that aims to solve the problem — how can different AI agents trust each other? As more apps are being built entirely without human intervention, AI agents are able to do almost everything needed to execute successfully: ideate, create, purchase, and build. However, while a human
Discover how x402 enables AI agents and APIs to make per-request stablecoin payments instantly, removing human intervention and scaling programmatic workflows.
As it becomes increasingly possible to use AI agents to create actual, working products, teams building for the crypto industry must find the right tools to give their agents enough reliable data. Because even though LLMs are incredibly advanced, they’re not actually able to parse and use raw blockchain
Crypto applications run on blockchain technology, but they are really built on data. Every wallet balance, trade, liquidation, NFT mint and protocol interaction ultimately depends on how the raw blockchain execution is captured and interpreted. We call that system crypto data infrastructure. Crypto data infrastructure is the system that transforms
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A practical guide to onchain data reconciliation for accounting, covering data sources, reconciliation tasks, system architecture, audit readiness and build vs buy decisions.
Crypto transaction monitoring is the continuous analysis of onchain activity to detect risk, fraud and possible compliance issues — and it operationally differs from traditional financial transaction monitoring. Blockchains are public, immutable ledgers that allow you to see every transaction, but there’s a big difference between seeing how pseudonymous transactions
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Blockchain networks generate enormous amounts of raw, onchain data — every transaction, smart contract interaction, and balance update is recorded on the public ledger. But accessing this data in an understandable way is not as simple as just scrolling through a spreadsheet until you find what you need. All blockchains run
Andrew Duca on handling crypto taxes for Solana LPs, Bitcoin Runes, and the long tail of onchain activity Crypto tax software faces a structural coverage challenge. Products built between 2017 and 2021 optimized for a specific market structure: centralized exchange trading, simple token swaps, and established protocols with stable transaction
A joint perspective from Uniswap Labs and Allium on the infrastructure enabling institutional DeFi adoption The institutional conversation around trading onchain has shifted from "if" to "how" over the past 18-24 months. What was once viewed as experimental infrastructure for retail traders now represents a