VAST Data’s DataEnclave secures AI against sensitive enterprise data, OpenAI’s GPT-6 Sol and Luna cut API prices by 50%, and Progress Software closes a $400 million Domo acquisition. Scroll down to catch the signals that matter.

🛡️ VAST Data Enclaves Confidential AI

VAST Data’s DataEnclave creates a hardware-isolated runtime for models working with sensitive enterprise information. Cryptographic attestation verifies policies before proprietary models and data enter protected CPU and GPU memory, while ecosystem partners support broader deployment. The capability is previewing now and expected through participating OEMs.

Confidential computing could make protected enterprise data far more usable for AI.

☀️ OpenAI Makes GPT-6 More Affordable

OpenAI’s GPT-6 Sol and Luna bring GPT-6 capabilities to the API, Codex, and ChatGPT Work, targeting faster, lower-cost workloads. OpenAI says improved caching and inference efficiency enable 50% lower API prices than GPT-5.6 promotional pricing, potentially expanding experimentation and production adoption.

Lower model costs could intensify competition for everyday AI workloads.

💸 GPT-6 Pricing Resets API Economics

OpenAI’s pricing reduction for GPT-6 Sol and Luna lowers API costs by half versus GPT-5.6 promotional pricing. The move matters beyond headline savings: developers can test more agents, process larger workloads, and revisit applications previously constrained by inference budgets, while customers gain stronger leverage in model selection.

Cheaper inference raises expectations for value across the entire model market.

🧩 JetBrains Builds an Agentic Development System

JetBrains’ Air system connects agentic development across integrated development environments, delivery workflows, and organizational governance. Rather than treating coding agents as isolated tools, the open system frames them as coordinated participants in software production, with controls intended to align experimentation, deployment, and enterprise oversight.

The strategic shift is from coding assistants toward governed software-production systems.

🌐 Progress Completes $400 Million Domo Deal

Progress Software completed its Domo acquisition, paying $400 million for substantially all of Domo’s AI and data-platform assets while assuming certain liabilities. The business will join Progress’s data-platform portfolio, strengthening capabilities for connecting, governing, and activating enterprise data across secure AI and agentic initiatives.

The transaction consolidates data context and control inside a broader AI infrastructure strategy.

🤖 Red Hat Reworks Ansible for AI Orchestration

Red Hat’s Ansible Automation Platform 2.7 introduces architectural changes supporting AI orchestration and visual environment building. The updates aim to simplify how teams design, upgrade, and govern automation environments, helping organizations connect intelligent decision-making with repeatable operational workflows rather than isolated demonstrations.

Automation platforms are becoming control layers for coordinated AI operations.

🇮🇩 Indonesia Targets Sovereign AI Infrastructure

TelkomGroup and Danantara are advancing sovereign-AI infrastructure in Indonesia, with plans targeting as much as one gigawatt of data-center capacity. The initiative links national infrastructure ambitions with local control over AI workloads, capacity planning, and data environments as demand for strategic computing continues to rise.

Sovereign AI is increasingly being measured in power capacity as well as policy.

🏭 Acceldata Launches a Private AI Factory

Acceldata’s xFactory is designed as a private software factory for building, testing, and deploying governed AI applications. It translates business intent into development workflows over federated data, emphasizing control and repeatability while helping organizations move from individual experiments toward managed application production.

Governed factories could shorten the path from enterprise intent to deployable AI.

⚡ Alibaba Unveils Zhenwu V900

Alibaba introduced the Zhenwu V900 chip while outlining plans to expand global data-center capacity beyond 20 gigawatts by 2032. The announcement combines domestic silicon development with a massive infrastructure commitment, signaling Alibaba’s effort to control more of the compute stack powering cloud services and AI workloads.

Chip design and data-center scale are becoming inseparable competitive advantages.

🌱 Finland Plans Green AI Data-Center Power

3 E Network announced a green-energy architecture for its planned Finnish AI data center, targeting multi-megawatt operations supported by renewable power infrastructure. The project reflects growing pressure to match expanding AI compute with cleaner energy systems, making power sourcing and facility design central to data-center competitiveness.

Future AI campuses will compete on energy architecture as much as computing hardware.

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