Can Legacy Data Security Survive the Velocity of Autonomous AI Agents?

Brad Shimmin, VP and Practice Lead at Futurum, shares his insights on Bedrock Data’s launch of Agent DLP, a runtime data loss prevention tool designed to secure AI agents and MCP tool calls at machine speed.
The Software-Defined Vehicle is Winning the Compute War and Losing the Owner

Futurum analysts Olivier Blanchard and Brad Shimmin on the moment the car stopped being a car, and why the sharpest pushback isn’t about EVs, autonomy, or subscriptions at all. From Utilizing AI – Ep. 35, “Software-Defined Vehicles: Do You Really Own Your AI Car?”
WEKA Engineers the AI Chassis to Conquer the Inference Power Paradox

Brad Shimmin, VP and Practice Lead at Futurum, shares his insights on WEKA’s launch of the WEKApod 3 appliances and NeuralMesh 6 software. By taking total control of its hardware engineering, WEKA aims to solve the severe power and density constraints currently choking enterprise AI inference deployments.
Solving the Distributed AI Dilemma: Oracle Base Database Cloud@Customer Brings OCI Automation to Local Workloads

Brad Shimmin at Futurum analyzes Oracle’s launch of Base Database Cloud@Customer X11, exploring how converged application VMs and local AI Database 26ai deployments solve data gravity and latency issues.
RegattaDB Arrives: A Unified Engine Built for the Era of Read-Write AI

Brad Shimmin, VP of Data Intelligence, Analytics, and Infrastructure at Futurum, explores Regatta’s launch of RegattaDB. By unifying OLTP, OLAP, and vector workloads, this new architecture provides the low-latency core required to power read-write autonomous AI agents.
The Active Storage Revolution: VAST and Cloudera Team Up to Cure Enterprise GPU Starvation

Brad Shimmin, VP and Practice Lead at Futurum, explores the new strategic partnership between VAST Data and Cloudera. By integrating the VAST AI OS with Cloudera data services, the vendors aim to eradicate ETL complexity and eliminate GPU starvation.
AWS Looks to Collapse the Search-Analytics Divide: How Its New OpenSearch Engine Fuels Agentic AI

Brad Shimmin, VP at Futurum, explores how AWS is re-architecting Amazon OpenSearch Service. By fusing search and analytics and integrating native MCP support, AWS aims to slash log storage costs by 70% while fueling autonomous AI agents.
Databricks Data + AI Summit: Looking Beyond the Database Through Unified Transactions, Analytics, and Agentic AI

Brad Shimmin, Chief Analyst at Futurum, shares his insights on Databricks’ 2026 Summit announcements, detailing how the unification of transactional and analytical data via LTAP lays the groundwork for truly autonomous agentic AI.
GenAI Workflow Benefit Drops 6pts as Docs, Automation, and Code Gains Rise

Brad Shimmin, VP & Practice Lead of Data Intelligence, Analytics & Infrastructure, reveals GenAI workflow efficiency fell 6.0 points as a perceived benefit, while measurable tasks like documentation (+4.9), automation (+3.8), and code (+3.2) gained.
Can Zoho’s Nathu La Server Redefine Enterprise Stack Sovereignty and TCO for AI?

The Futurum Group’s Keith Kirkpatrick and Brad Shimmin share their insights on Zoho’s Nathu La server, and discuss the impact on the SaaS market, end customers, and Zoho’s competitors.
Collate Turns OpenMetadata Into a Persistent Semantic Memory Layer for Enterprise AI Agents

Brad Shimmin, VP and Practice Lead at Futurum, examines Collate 2.0’s AI-native semantic context layer built on OpenMetadata, and what it means for enterprise AI readiness, data governance, and the open catalog landscape.
From Storage to Action: Why Autonomous AI Is Forcing a Database Revolution

Brad Shimmin at Futurum shares his insights on how the shift to autonomous, read-write AI agents is forcing legacy databases to evolve. Discover why strong consistency, multi-tiered memory, and speculative branching are the new mandatory benchmarks.
