Key takeaways: * Financial institutions can’t use natural language prompts alone to get reliable outputs * Prompts are not reproducible or auditable on their own * MCP acts as the “USB-C” for AI * Institutions need to use MCP with a structured data layer to get trusted outputs 💡What is MCP (Model Context
The CLARITY Act is closer than ever to passing into law. Just last week, the bill made it out of the Senate Banking Committee, a year after it was first introduced last May. Even with bipartisan discord, (and plenty of reservations still regarding the bill’s regulation of stablecoin yield
How you pick a supply denominator moves a crypto valuation more than most other assumptions. Using HYPE as the worked example. For HYPE, the same business value we estimate at $25.8B, divided across six candidate supply numbers, produces price targets from $26 (FDV) to $105 (circulating only) per token.
Dune is retiring the SIM API on August 1, 2026. If your app uses SIM for wallet balances, transaction history, or DeFi positions, you need a replacement before that date. Allium's Real-time API covers the same endpoints. 23 chains. Full data lineage on every response. Here's
Key takeaways: * A stablecoin supply number without methodology context is meaningless. * Allium breaks it down into: total supply, issuer-reported supply, and adjusted supply * Payment providers, DeFi protocols, stablecoin issuers all need different supply numbers for their own unique reasons * Allium provides the flexibility to get the exact number you need
Key takeaways: * Compliance systems flag risk, but they rarely explain it * Passing a compliance check doesn’t mean understanding counterparty behavior * Intelligence systems turn activity into explainable patterns and decisions * Both layers depend entirely on the quality of the underlying data 💡What’s the difference between crypto compliance and crypto
Key takeaways: * Blockchain data needs a system with multiple layers to be compliant * Most companies are missing that data foundation unifying interpretation * Data without standardized interpretation can cause huge differences in a compliance stack * AI systems need normalized, standardized data to function without human interference * Crypto compliance data stacks now
Key takeaways: * APIs are simple and fast, but limited to predefined queries * SQL enables flexible, composable queries that align with how AI systems operate * Blockchain data is difficult to serve via APIs without heavy normalization and standardization across chains and protocols * Most meaningful blockchain metrics (balances, positions, flows) must be
Key takeaways: * More crypto analytics and investigations are being assisted by AI * AI systems can use MCP to turn prompts into defined operations * AI can still hallucinate with MCP, risks are still involved * The quality of the data layer will determine the quality of the crypto investigation or analysis 💡What
Key takeaways: * No crypto systems should rely on infrastructure that creates a single point of failure * But data accuracy matters just as much — blockchain data needs to be a system of record for projects to be fully protected * Verification didn’t fail in isolation. The issue was the state it
Key takeaways * Blockchains don’t provide data in the right format to easily build crypto wallets * Many blockchain data platforms have siloed data tools, complicating the wallet building process * PnL is the most difficult problem to solve when building a crypto wallet * Allium provides one platform that simplifies the wallet
Key takeaways: * Crypto wallets used to only need to send, receive, and show balances * The crypto industry’s growth means that users require more from their wallets — like portfolio views, trading capabilities, staking, strategic AI assistance * Traditional wallet infrastructure wasn’t built to support this level of execution * Allium’s