Blockworks Acquires Messari to Unify Crypto Data Infrastructure

Blockworks has acquired Messari after securing a $192 million valuation earlier this year, deepening its push into crypto data infrastructure as competition intensifies to build the industry’s information layer. According to an announcement from Blockworks, the deal combines two of…

Crypto data and media company Blockworks has acquired rival research platform Messari at a discount to its prior valuation, the Wall Street Journal and Bloomberg reported Friday. The deal joins two of the most prominent names in the crypto intelligence space.

Blockworks has acquired Messari as it expands into crypto data infrastructure, issuer tools, and market intelligence for onchain assets. The post Blockworks buys Messari in push to build onchain market data layer appeared first on Crypto Briefing.

Misinformation risks damaging credibility and trust, highlighting the need for rigorous fact-checking and responsible journalism practices. The post Blockworks acquires rival Messari for over $10M appeared first on Crypto Briefing.

The acquisition could reshape the crypto data landscape, potentially setting a new standard for integrated services in the industry. The post Blockworks acquires rival Messari to expand crypto data services appeared first on Crypto Briefing.

The acquisition follows leadership changes and layoffs at Messari and adds one of crypto's largest data and analytics platforms to Blockworks' growing research business.

I’ve seen a lot of promising AI prototypes fall apart after launch. And it’s rarely because the model was bad. More often, the problem starts much earlier; teams treat the data layer like something they can figure out later. They’ll spend weeks fine-tuning prompts, testing models and debating evaluation scores, then throw together the retrieval pipeline over a weekend and move on. At first, everything looks great in demos. But a few months later, the system gives outdated answers; the embeddings no longer match the source documents, and nobody fully understands what changed. What started as an impressive prototype slowly becomes difficult to trust in production. The teams that avoid this tend to realize one thing early: Embedding pipelines are fundamentally a data engineering problem, not an entirely new AI discipline. It’s still ETL (Extract, Load, Transform) at its core, but with embeddings and vector stores as the destination instead of a warehouse. Once you start looking at it that

Messari Q1 2026 data shows 27.1% growth in Akash leases, 45% revenue compression, and BME activation. What signals could prove real utilization next?