Most enterprise AI tools hallucinate on your internal documents because they have never seen them. NotebookLM Enterprise changes the equation by grounding every answer in your actual content, inside your GCP environment.
The Hidden Tax on Every AI Training Run
Accelerator utilization rates below 70% are not a GPU problem. They are a storage problem. Google Cloud’s Hyperdisk ML changes that with multi-attach volumes and sub-millisecond training data latency.
Their Data Was Everywhere. Now It Isn’t. (PayPal)
PayPal completed one of the largest data migrations in history, consolidating 400 petabytes of fragmented data into BigQuery. The goal was not just cleaner infrastructure; it was the foundation for everything AI-powered that comes next.
Google Built a TPU for the Age of Inference. Meet Ironwood.
TPU Ironwood is Google’s 7th-generation custom AI chip, and unlike its predecessors, it was built for inference first. Here’s what that means and why it matters.
MCP Is the New REST. Google Cloud Just Made It Enterprise-Ready.
The Model Context Protocol is becoming the standard for how AI agents call external tools. Google Cloud Managed MCP Servers handle the enterprise governance layer so you don’t have to.
Apigee Got a New Job: The Control Plane for Your AI.
Apigee evolved from API gateway to the control plane for LLM traffic, agent actions, and MCP tools. Here is why that matters for anyone building AI features at scale.
A2A Is How AI Agents Finally Learn to Play Nicely
Google’s Agent2Agent protocol, now under Linux Foundation stewardship, gives AI agents a standard way to find, authenticate, and collaborate with each other across any vendor or framework. For ISVs, it changes what a multi-agent product architecture can look like.
Google Releases Gemma 4. Now What?
Gemma 4 is Google’s first fully open-source multimodal model family, released under Apache 2.0. For ISVs, that changes the calculus on how you build and what you ship.
GPU Inference Without the Cluster. Cloud Run Finally Makes That Real.
Cloud Run now supports GPUs with scale-to-zero billing. For AI inference workloads that are bursty, sporadic, or just getting started, that changes the math entirely.
Google Distributed Cloud: Running Gemini Where the Internet Can’t Go
Google Distributed Cloud Air-Gapped puts Gemini LLMs inside fully air-gapped defense and sovereign environments. The internet has no path in. Here is how it works.
AI That Understands Your Entire Codebase?
Gemini Code Assist Enterprise gives your engineering team an AI that understands your private codebase, your GCP infrastructure, and your org’s coding standards. For ISVs, it is the difference between faster typing and actually shipping faster.
AI Changes the Attack Surface. Your Security Layer Needs to Keep Up.
Prompt injection is the SQL injection of the AI era. Model Armor is the first cloud-native solution that protects any LLM, on any cloud, without locking you into a single vendor.
What GKE Inference Gateway Does That No Other Load Balancer Can
Standard load balancers treat LLM inference like any other HTTP traffic. That is expensive and slow. GKE Inference Gateway knows the difference.
Safety Audits That Took 14 Days Now Take One Hour (AES)
AES ran more than 1,500 safety audits a year the hard way. With Anthropic’s Claude on Vertex AI, the same work now takes one hour instead of 14 days, at 99% lower cost.
One Database. Transactions, Analytics, and Vector Search. No Pipelines.
AlloyDB collapses three separate database systems into one managed PostgreSQL instance. The benchmarks are embarrassing for Aurora.
The ETL Pipeline You’re Running Probably Shouldn’t Exist
BigQuery can now run AI models directly inside SQL. The implications for how you’ve been architecting your data stack are a little uncomfortable.
28,000 Customer Care Reps. One AI That Makes Them All Better. (Verizon)
Verizon deployed Gemini-powered AI across 28,000 customer care reps, achieving 95% answerability for customer inquiries. Here’s what that architecture looks like and why it matters for ISVs.
Wait, Oracle Runs Inside Google Cloud?
Oracle and Google Cloud put actual Exadata hardware inside GCP data centers. That is a strange sentence to type, and it has some interesting implications.
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