January 22, 2026

AI’s biggest bottleneck isn’t the models—it’s the data. Legacy ETL-era architectures were built for slower, static workloads, and they’re now failing on both security and speed. As AI demands real-time, controlled access to data, it’s time to rethink how data is accessed entirely.

December 16, 2025

Discover why AI initiatives slow down after initial pilots and what's really needed to scale AI across the enterprise.

September 2, 2025

API-driven data sharing powers modern digital innovation, but every new endpoint also introduces risk. Recent breaches caused by exposed API keys show how easily sensitive data and AI infrastructure can be compromised. To innovate safely, organizations need disciplined API security practices and governed data access layers that enforce policy, limit exposure, and log every request by default.

September 1, 2025

As GenAI becomes embedded in fintech, health tech, and other regulated products, identity—not just authentication—becomes the foundation of data security. Dymium enables identity-aware, context-driven access control so every AI prompt, API call, and agent interaction is governed dynamically, enforcing least-privilege access without slowing innovation.

August 18, 2025

Zero-copy data access lets analytics, BI, and AI systems query data directly at its source without duplication or ETL. This enables real-time insights, lower storage and pipeline costs, and stronger governance. Modern platforms like Salesforce Data Cloud and ServiceNow now deliver production-ready zero-copy access on top of Snowflake and Databricks.

August 18, 2025

Vendor sprawl is quietly draining IT budgets and increasing security risk. Fragmented data stacks drive operational overhead, duplicate tooling, and governance blind spots. As organizations push to consolidate vendors, unified data access platforms are emerging as a way to simplify architecture, reduce cost, and strengthen compliance—proving that leaner stacks deliver greater control and velocity.

July 9, 2025

As enterprises scale AI adoption, they face a growing challenge: enabling broad data access while meeting strict security and compliance requirements. By applying Zero Trust principles—least privilege access, continuous monitoring, and real-time policy enforcement—organizations can protect sensitive data while allowing AI systems to operate effectively and responsibly.

July 9, 2025

In-place governance enables organizations to enforce security, privacy, and compliance policies directly at the data source—without moving or duplicating data. By applying real-time access controls, masking, and auditing where data already lives, teams can meet regulatory requirements while preserving agility, performance, and innovation.