Welcome back to the World of DaaS Roundup. This week’s signals from across the data economy highlight three shifts:
→ Regulation is reshaping access
→ Data is becoming a product
→ Infrastructure is powering the AI era
🏢 DATA IS BECOMING A PRODUCT
AI startup Mercor offers to buy workers´past job data for model training. The WSJ
→ Mercor is paying professionals for their past work (including proprietary materials) to use as AI training data, signaling a shift toward direct data acquisition as a core input for model development.
U.S. agencies expand use of commercially available data from brokers AI and surveillance systems. NPR
→ U.S. agencies are increasingly buying datasets from data brokers, reinforcing how personal Dara is being packaged, priced, and traded as a scalable asset for AI.
🔐 REGULATION IS RESHAPING ACCESS
U.S. states intensify scrutiny on ´surveillance pricing´ powered by consumer data. Reuters
→ Regulators in states like California and New York are investigating how companies use consumer data (location, behavior, purchase history) to set personalized prices, signaling tighter control over how data can be use commercially.
🏗️ INFRASTRUCTURE IS POWERING AI ERA
Microsoft builds its own AI model stack to reduce OpenAI dependence. Forbes
→ Microsoft is launching in-house AI models across modalities, signaling a shift toward owning its full AI stack and reducing reliance on external providers like OpenAI.
Big Tech’s $635B AI spending faces energy and costs constraints. Reuters
→ Major tech companies are projected to spend up to $635B on AI infrastructure, but rising energy costs and supply constraints are emerging as key limits to scaling compute.
Re-Air: Data Tools, Templates, and the Trouble with “Easy” Solutions.
The trade-off between speed, control, and long-term flexibility in modern data stacks — The Data Stack Show.
→ As low-code tools and SaaS platforms simplify data workflows, companies are accelerating implementation at the cost of flexibility, revealing how infrastructure decisions directly impact control, scalability, and the ability to truly own and monetize data.
In this episode of The Data Stack Show, they discuss:
• Why “easy” data tools often create hidden complexity, limiting customization and long-term scalability.
• The trade-offs between buying vs building data infrastructure, and how these decisions
affect control over data systems.
• How platform lock-in is becoming a critical constraint, shaping how companies manage and monetize their data.
• The role of templates and pre-built solutions in accelerating adoption—but also standardizing and limiting differentiation.
• Why infrastructure choices today determine how data can be accessed, governed, and leveraged as a strategic asset in the future.
M&A Funding Roundup
· Signal AI acquired Memo (to add real readership data into its platform)
· Supplier.io acquired TealBook (to strengthen its supplier dataset).
· Coastal Measures raised $1.2M (pre-seed) (to standardize coastal and ocean data).
· Ridge AI raised $2.6M (pre-seed) (to build AI-native analytics for product teams).
· Head of Data Content and Distribution (Investor Services) - Managing Director, Citi
· Director, Data Acquisition, Mastercard
· Strategy & Analytics Associate, Sentilink
· AI Strategy and Process Lead, Sentilink
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