All news with #agentic ai tag

🔎 Google is evolving Dataplex into the Knowledge Catalog, an always-on context engine that supplies AI agents with business semantics, entity relationships, and governance to reduce hallucinations and latency. It aggregates metadata across Google services and third-party catalogs, ingests LookML and BigQuery measures, and packages governed data products for production use. Enrichment via multimodal extraction and Gemini plus access-aware, high-precision semantic search helps agents retrieve authoritative context in real time.

🚀 At Google Cloud Next '26, Looker was updated to enable Agentic BI through deeper integration with Gemini and BigQuery, introducing conversational agents that can trigger downstream business actions. New agents include upgraded Conversational Agents, Dashboard Agents, embedded conversational experiences, and Agentic Workflows. The release also modernizes the UI with AI-powered self-service tools like Visualization, Expression, and Insight Assistants. Emphasis is on governed semantic layers, open protocols, and developer tooling to reduce hallucinations and accelerate model-driven analytics.

🧭 Google announced the Agentic Data Cloud, an AI-native architecture that integrates models, analytics, and operational databases to ground agentic applications in trusted, real-time data. The release emphasizes embedding AI across the data stack, unifying transactional and analytical workloads, and simplifying enterprise deployments. New developer tools include Vibe coding integrations with Google AI Studio, modular Tools for Data Agents and onboarding/observability agents, while AlloyDB gains large-scale vector search and optimized in-database AI functions.

🔒 Google announced new capabilities for Google Distributed Cloud (GDC) at Next ’26, bringing Gemini models and an advanced AI stack to on-premises and edge deployments. GDC offers air-gapped and connected deployment models on Google-supplied or customer hardware, and now supports NVIDIA Blackwell GPUs, expanded machine families, and increased storage and I/O. The release adds an AI gateway for optimized inferencing — with dynamic routing, load balancing, quota controls and observability — and a sovereign agentic AI architecture on Kubernetes to run autonomous, secure agents entirely within customer boundaries.

🚀 Google Cloud announced a set of compute updates at Next ’26 designed to run agentic AI alongside general-purpose workloads with improved performance and lower cost. Highlights include GA for Axion N4A CPUs and GKE Agent Sandbox on Axion N4A, preview of bare-metal C4A.metal, expanded Intel Xeon 6 C4 shapes, and new high-throughput networking and Hyperdisk storage options. These changes aim to provide adaptive, secure execution sandboxes, greater I/O and network bandwidth, and flexible pricing to avoid provisioning bottlenecks and reduce TCO.

🧭 Oracle AI Database@Google Cloud brings Oracle's mission-critical databases natively into Google Cloud to enable direct pipelines from enterprise records to the AI layer. The announcement expands regional availability, introduces an Oracle AI Database Agent for Gemini interaction, and integrates with Database Center, Knowledge Catalog, OCI GoldenGate, and VPC Service Controls. These features aim to lower latency, simplify governance, and make Oracle data actionable for agentic AI workflows.

🤖 Google announced its AI Hypercomputer — a unified infrastructure stack built to support agentic AI — at Google Cloud Next. The announcement bundles new hardware and software, including TPU 8t and TPU 8i, A5X GPU instances, Axion N4A CPUs, the Virgo Network, and major storage and GKE upgrades. Google says the stack is designed to accelerate training and inference, reduce latency, and improve cost and energy efficiency for large-scale, agent-native applications.

🚀 Google Cloud is expanding its partner ecosystem to accelerate the Agentic Enterprise with new funding, technologies, and integrations. The company announced a $750 million innovation fund and the Gemini Enterprise Agent Platform with an Agent Gallery to surface vetted partner-built agents. It is deepening technical alliances with global consulting firms, embedding forward deployed engineers with integrators, and extending Gemini across major SaaS platforms to speed enterprise adoption.

🛡️ Google Cloud and Wiz outline agentic defenses, platform protections, and integrations to secure AI and multicloud workloads. At Next '26 they introduced preview and GA features including Threat Hunting, Detection Engineering, and Triage and Investigation agents, plus the Gemini Enterprise Agent Platform for agent governance. These innovations aim to automate detection, reduce analyst toil, and protect AI development and runtime across clouds and SaaS environments.

🚀 Google Cloud at Next '26 introduced a cross-cloud infrastructure blueprint designed for the agentic AI era, combining fluid compute, secure cross-cloud connectivity, a unified data layer, and digital sovereignty. Announcements include new CPU families (C4N, M4N with Hyperdisk Extreme), GKE Agent Sandbox, Agent Gateway, Smart Storage, Knowledge Catalog, and Confidential External Key Management to enable high-performance, governed agent workflows across clouds and on-premises. The updates target enterprises and public sector organizations preparing for machine-speed AI operations.

🤖 Google Cloud introduced a next-generation cross-cloud Lakehouse engineered for the agentic AI era. It combines fully managed Apache Iceberg storage with read/write interoperability, a high-performance Managed Service for Apache Spark, and BigQuery integration to run multimodal workloads in real time. The service adds cross-cloud interconnect and caching to access AWS and Azure data with low latency, and unified governance via Knowledge Catalog to secure and profile data. Customers like Spotify and partners such as Accenture are already testing the platform.

🚀 Gemini Enterprise is an end-to-end system for the agentic era, combining access to frontier models, a developer platform, a collaborative app, and a partner ecosystem to build and deploy agent fleets. The offering centers on the Gemini Enterprise Agent Platform — an evolution of Vertex AI — with an enhanced Agent Development Kit (ADK), graph-based orchestration, persistent Memory Bank, and fast Agent Runtime for multi-step work. IT teams gain a unified control plane for identity, governance, Model Armor, and auditing, while knowledge workers use a no-code Agent Designer, Inbox, Projects, and Canvas to create and monitor agents.

🎯 GEAR, powered by Google Skills, delivers hands-on AI training to help professionals design, build, and deploy enterprise-ready agents. Members receive 35 monthly learning credits, access to a Discord community, curated agentic resources, and free Google Cloud certification prep for customers. GEAR will be deeply integrated into Google Cloud Next ‘26 with mini-labs, learning paths, expert workshops, and gamified activities to accelerate practical, production-oriented skills.

⚠️ Research from the Cloud Security Alliance (CSA) and Token Security warns that unchecked AI agents have caused widespread cybersecurity incidents across enterprises in the past year. The report finds many organizations overestimate agent visibility — 68% claim high visibility while 82% discovered unknown agents — leading to data exposure, operational disruption and financial losses. It highlights weak lifecycle governance, particularly around decommissioning, and calls for unified controls across discovery, policy, monitoring and decommissioning.

🤖 Over eleven months Cloudflare built an internal AI engineering stack that integrates AI Gateway, Workers AI, the Agents SDK, and developer tools like OpenCode and Backstage. The platform centralizes authentication with Cloudflare Access, routes model traffic and costs through AI Gateway, and runs inference on Workers AI to reduce latency and expense. The deployment includes an AI Code Reviewer and an Engineering Codex to enforce standards and maintain quality at scale.

🤖 Cloudflare's Agents Week highlights a broad set of primitives, services, and developer tooling to support agents as first-class workloads on the Cloudflare Workers platform. Key compute advances include Artifacts, Sandboxes GA with programmable egress, Durable Object Facets, and Workflows v2 to scale background agents. Security features—like Cloudflare Mesh, Managed OAuth for Access, and resource-scoped permissions—aim to make secure agent deployment the default while an expanded Agent Toolbox adds inference, memory, voice, email, and browsing capabilities to help builders move prototypes to production.

🔎 Cloudflare launches isitagentready.com and a companion Cloudflare Radar dataset to measure and accelerate adoption of emerging AI agent standards across the web. The tool scores sites on Discoverability, Content, Bot Access Control, and Capabilities, and returns actionable prompts for each failing check. The site publishes machine-readable endpoints (MCP server, agent-skills index) so compatible agents can scan and remediate programmatically. Cloudflare also refactored its developer docs to serve Markdown and curated LLM resources, producing measurable reductions in token usage and latency.

🧠 Cloudflare announces Agent Memory, a private beta managed service that extracts information from agent conversations and makes it available without filling model context windows. The service offers persistent profiles with operations to ingest conversations, explicitly remember or forget items, and recall synthesized answers, integrating with Cloudflare Workers and a REST API. Agent Memory uses a retrieval-based architecture with deterministic ingestion, multi-stage verification, vector and full-text retrieval channels, and Reciprocal Rank Fusion to synthesize concise, contextual responses. Memories are classified, versioned or superseded as appropriate, and fully exportable so organizations retain ownership.

🛡️At VirusTotal we are integrating reputation and Code Insight directly into AI agent decision loops so agents can consult verdicts and context as part of their runtime behavior. Two community plugins, VT-sentinel (OpenClaw) and hermes-virustotal (Hermes), demonstrate the approach using the new VTAI API with compact responses and per-agent identities. Both MIT-licensed projects scan files, annotate hashes, and provide configurable privacy and enforcement presets so agents can quarantine, block, or proceed based on risk appetite.

🎬 At NAB Show 2026, Google Cloud presents an agentic media platform that embeds AI across production, distribution, and monetization. Partners such as Avid (Content Core), Backlight (Iconik), and Brahma.ai showcase cloud-native tools that add searchable metadata, AI-driven editing assistants, and secure digital likenesses. The ecosystem also highlights Bitmovin, VionLabs, and Zixi to optimize delivery, discovery, and broadcast reliability.