Amazon Bedrock announces up to 80% lower prices for OpenAI GPT‑5.6 models
Luna drops 80% and Terra drops 20%—your high-volume AI workloads on Bedrock just got dramatically cheaper, automatically.
Luna drops 80% and Terra drops 20%—your high-volume AI workloads on Bedrock just got dramatically cheaper, automatically.
Government and regulated-industry teams can now run xAI's reasoning-optimized Grok 4.3 inside AWS GovCloud with configurable cost controls.
Government workloads can now use Gemma 4's reasoning, multimodal, and agentic capabilities inside FedRAMP-compliant AWS GovCloud.
All SageMaker Unified Studio tools now get real Git branching, commits, and multi-repo support — including Notebooks, which had none before.
Investigate AWS Security Hub findings via natural language and interactive attack-path graphs—directly inside Claude Desktop, at no extra cost.
Opus 5 brings overnight-capable agents, 1M-token context, and ZDR-by-default to AWS—raising the ceiling for enterprise AI workloads.
Government teams can now run Opus 4.8 and Sonnet 5 inside GovCloud with full audit-ready usage monitoring and data residency guarantees.
Now you can objectively score any AI agent on real AWS tasks — provisioning, troubleshooting, and diagnosis — using live cloud environments.
Debug AI agents faster — all traces, prompts, and logs now land in one per-agent CloudWatch log group with CMK and IAM scoping support.
Government workloads can now access Claude Sonnet 5's coding and agentic power inside GovCloud's strict data-residency boundary.
Deploy 70B-parameter LLMs on a single instance with 2.3x faster inference, now available in Seoul, Tokyo, and London.
Government agencies can now run GenAI inference on faster NVIDIA L4 GPUs within GovCloud's compliance boundary, at up to 2x the performance of G4dn.
G7's Blackwell GPUs bring 4.6x faster inference and 32 GB GPU memory to SageMaker, letting you serve 7B–30B models without over-provisioning or quantization.
SQL Server 2025 on RDS adds native REST-from-T-SQL, vector data types, and expanded Standard Edition limits—enabling AI workloads without re-architecting apps.
Query OpenSearch logs and metrics alongside Redshift and S3 data in one governed workspace—no tool switching required.
Track AI coding agent ROI, token spend, and PR velocity across teams—all in CloudWatch, with no extra instrumentation needed.
FinOps teams can now slice Bedrock costs by model, token type, and inference mode natively in CUR 2.0—no custom parsing required.
AI agents now automate SCA and AGI fund requests end-to-end, cutting manual work and eligibility errors across all AWS Partner funding programs.
Mixed-instance HyperPod clusters now auto-apply optimal GPU network topology per Slurm partition, boosting distributed training throughput with zero config.
Data engineers can now publish reusable, no-code ETL transforms to a shared team library, enforcing consistent business logic across all pipelines.
Describe your OpenSearch goal in plain English and let AI coding agents handle provisioning, search, logs, and traces — no infra changes needed.
GuardDuty now detects prompt injection, cost harvesting, and anomalous Bedrock/SageMaker activity—no custom tooling required.
Security Hub now auto-discovers managed, self-hosted, and third-party AI assets org-wide and links them to live threats—at no extra cost.
One click in the Lambda console now fully configures any major coding agent with serverless best practices, skills, and MCP server—no doc-hunting required.
AI coding agents can now troubleshoot, scale, and build Flink apps on AWS without deep Flink expertise — here's how.
AI agents can now provision, migrate, tune, and review DocumentDB clusters using 7 built-in expert workflows—with full IAM and CloudTrail guardrails.
Google DeepMind's multimodal Gemma-4-E2B-it—with vision, audio, reasoning, and function calling—is now one click away on SageMaker JumpStart.
Deploy OpenAI's PII detection model on your own AWS infrastructure in minutes—keeping sensitive data out of your AI pipelines without leaving your account.
Deploy Mistral's streaming speech model inside your own AWS account — real-time, multilingual, with tunable latency vs. accuracy trade-offs.
Build multimodal, multilingual search pipelines on AWS using a vision-language embedder and instruction-tunable reranker, deployable in minutes via JumpStart.
Three-tier GPT-5.6 family lands on Bedrock with 90% prompt caching discounts and AWS-native billing — Sol leads coding and cybersecurity benchmarks.
Bake security agents and custom drivers into HyperPod Slurm nodes at the image level — faster startups, zero config drift, enterprise compliance met.
AI-powered root cause analysis and code fixes for failed Spark jobs now available across all EMR deployment options, including EKS.
Skip the S3 scripts entirely — HyperPod now auto-configures Slurm nodes from an AMI as capacity scales in, cutting setup time and ops overhead.
Catalog any asset format—PowerBI dashboards, medical images, PDFs—inside SageMaker Unified Studio with governed discovery and subscription workflows.
Batch-write thousands of features in one API call and list records natively — no custom tooling needed for scale ingestion or audits.
AI agents can now authenticate to AWS MCP Server via standard OAuth — no CLI or extra software needed, with full IAM governance intact.
Validate every GPU node before it runs a job — deep health checks now work with async continuous provisioning to prevent silent hardware failures.
191 new managed rules bring native compliance checks for Bedrock AI agents, SageMaker, ECS, RDS, and more—no custom code required.
AI now writes your sales plays, call scripts, and emails for each AWS lead — personalized to your solutions and the customer's industry.
19 new no-code operators let you orchestrate Bedrock, S3 Vectors, Glue, and MWAA together — without writing a single line of DAG code.
Federal and regulated workloads can now run serverless, billion-vector AI search within GovCloud compliance boundaries at up to 90% lower cost.
IAM-based SageMaker domains now get full data lineage with column-level tracking, interactive graphs, and a new event deletion API.
Run GenAI, vector search, and natural language SQL natively inside Oracle—no extra infrastructure, no data movement required.
Connect your existing MWAA environments to SageMaker Unified Studio — no DAG migration needed, with Airflow 3 visual authoring included.
Separate prefill and decode onto dedicated GPU pools to eliminate token-generation stalls and cut per-token latency under heavy concurrency.
Skip hours of AWS setup — go from any Hugging Face model to a GPU-ready SageMaker Studio environment in one click.
Platform teams can now provision SageMaker Unified Studio domains via Terraform IaC pipelines, enabling consistent, auditable multi-environment deployments.
HyperPod now auto-patches GPU nodes only when idle and lets you roll back full NVIDIA/CUDA stacks—keeping long training jobs safe and clusters secure.
AI-generated, citation-backed answers to compliance questionnaires — free, in minutes, sourced directly from AWS SOC, ISO, and C5 docs.
Run production AI agents with lower latency in Southeast Asia and Southern Europe—full AgentCore capabilities available from day one in all four new regions.
AgentCore now supports 5,000 concurrent agent sessions by default in primary US regions, letting teams scale to production without quota increase requests.
AI agents can now automate legacy desktop apps—ERP, mainframes, CRMs—with full enterprise governance, no modernization needed.
New instances during scale-out now skip the ECR pull entirely, slashing minutes of cold-start latency for large GenAI containers automatically.
31 automated controls now continuously enforce security best practices across Bedrock, AgentCore, and SageMaker—no custom rules needed.
Near-Opus intelligence lands at Sonnet pricing — with a 1M context window, always-on reasoning, and two AWS access paths.
Fine-tune Gemma 4 on SageMaker AI with no cluster management — pay only for training time using SFT, DPO, or RFT.
Anthropic's most capable model now runs inside GovCloud, bringing 1M-token reasoning and agentic autonomy to regulated federal workloads.
GovCloud developers can now access GPT-5.4 and a cost-efficient open-weight Nemotron model for agentic coding inside AWS's secure boundary.
Skip the wait: CloudFormation Express Mode cuts deployment times up to 4x by completing once config is applied, not after full stabilization.
Write firewall rules using EKS namespaces and ECS attributes—no more broken IP rules when pods scale or restart.
Apply WAF rules once at the Gateway layer to protect all your AI agents, tools, and integrations from exploits and abuse in production.
Federal agencies and DoD programs can now use Kiro's agentic AI coding platform for sensitive workloads—compliantly, inside GovCloud.
Federal agencies can now run OpenAI GPT and NVIDIA Nemotron models on sensitive government data with full FedRAMP High and DoD IL-5 authorization.
G6e's 48 GB-per-GPU L40S hardware is now available in SageMaker notebooks, enabling interactive fine-tuning of 13B-parameter LLMs at 2.5x G5 speed.
Share a single AgentCore Memory resource across AWS accounts using resource-based policies—no more duplicating memory stores per account.
Two new automated workflows now refine your formal logic policies with far less manual effort, boosting hallucination detection accuracy.
Describe your migration goal in plain language and let an AI agent handle planning, infra deployment, and cutover—weeks of manual work, automated.
Run LLMs and spatial AI workloads on NVIDIA Blackwell GPUs with 96 GB/GPU memory directly inside SageMaker Studio notebooks.
GuardDuty now auto-investigates threats in minutes—with confidence scores, MITRE mapping, and fix recommendations—slashing manual triage time.
Teams can now @mention Claude directly in Slack channels with per-channel governance, async task delegation, and AWS spend commitment support.
Give every user or AI agent their own secure VM sandbox—fast startup, stateful sessions, zero infra management, all serverless.
Migrate workloads to any AWS commercial region—including 16 newly added—making data residency compliance far simpler.
AI coding agents can now guide MSK sizing, troubleshooting, and Kafka migrations—no Kafka expertise required.
Deploy a fast, compact embedding model for semantic search and RAG pipelines directly in your AWS account—no custom containers needed.
Mistral's compact 14B model brings multimodal vision, native function calling, and multilingual support to SageMaker JumpStart with one-click deployment.
Get instant LLM inference visibility — TTFT, GPU health, KV cache, and autoscaling — in one dashboard with zero instrumentation.
Quick's new autonomous agents handle your busywork 24/7—stalled deals, compliance alerts, POs—while you focus on what actually matters.
Turn production agent traces into validated fixes automatically—closing the gap between silent failures and confident, data-proven improvements.
Go from agent idea to production in minutes—no orchestration code required, with full model flexibility and built-in governance.
Enterprises can now block prompt injection and data leaks at the agent gateway perimeter—no code changes, full audit trail included.
Run fully managed Oracle Autonomous Database on AWS with zero infrastructure setup, serverless scaling, and native AWS service integrations.
Build production RAG agents over enterprise data—no vector DBs or pipelines to manage, with multimodal support and agentic multi-hop retrieval built in.
AI-powered STRIDE threat models generated automatically from your code or design docs — free during preview, right inside your IDE.
Security scans now prove exploitability via sandbox simulation—cutting false positives and bringing findings directly into Kiro, Claude Code, and major SCM platforms.
AI coding agents can now use AWS secrets at runtime without ever exposing plaintext values to the model, logs, or memory.
Mainframe modernization now goes from COBOL assessment to traceable cloud-native code in one automated workflow — cutting years of effort to months.
Real-time AI agents now score, enrich, and route every co-sell deal automatically—unlocking AWS field engagement faster than ever.
ISVs can now auto-generate, validate, and score AWS Marketplace listings from existing docs—cutting manual effort and boosting buyer discoverability.
Migrate shared storage workloads from NetApp, Dell, Pure Storage, or VMware to FSx for ONTAP—compute, network, and storage in one wave.
AI agents now automate AWS partner onboarding end-to-end—from profile setup to tax compliance to Marketplace listings—cutting weeks of manual research.
Apply per-step AI safety checks in agent loops without managing guardrail resources—get numeric risk scores and enforce your own thresholds.
Automatically assess and migrate your OpenAI, Gemini, or Anthropic workloads to Amazon Bedrock with production-ready code and cost comparisons.
Formal logic-based AI output validation with 99% accuracy and auditable guarantees is now available in Sydney for regulated industries.
AWS agents can now search the live web natively inside your AWS environment — no third-party APIs, no data egress, no extra setup.
16 new connectors—including Snowflake, Figma, WhatsApp, and Zapier—let teams automate cross-tool workflows without leaving Quick.
Attach up to 1 GB of queryable JSON/XML/YAML context per S3 object—no separate metadata system needed for AI agents or analytics.
Guarantee exact metadata values on agent memory records — enabling hard multi-tenant isolation and compliance boundaries without LLM inference.
DevOps Agent now runs scheduled SRE bots and plugs into any MCP/A2A tool—turning reactive ops into automated, composable workflows.
Publishers can now automatically charge AI bots per request at the CDN edge—turning crawler traffic into direct stablecoin revenue with zero code changes.
xAI's reasoning-first Grok 4.3 brings configurable reasoning effort and token efficiency to Bedrock — potentially cutting enterprise inference costs significantly.
Enterprises can now autonomously detect, prioritize, and fix tech debt across thousands of repos—including AI-readiness gaps—without manual effort.
Fine-tune a 30B NVIDIA model on your own data in days—no GPU cluster management, no upfront cost, just results.
Government and regulated-industry customers can now reserve cutting-edge NVIDIA B200/B300 GPU clusters inside FedRAMP-compliant GovCloud regions.
OpenAI's most powerful models land in AWS's largest region, bringing 272K-context agentic AI inside your existing AWS security perimeter.
Query Snowflake data and documents in plain language and automate compliance workflows—all from one AI workspace, in minutes.
Investigate incidents with AI agents inside VS Code or Claude Desktop, with interactive OpenSearch visualizations rendered inline—no browser switching needed.
Deploy tracing and security agents as host-aware ECS daemons—no more embedding privileged sidecars in every application task definition.
Three Gemma 4 variants—dense, MoE, and compact—bring built-in reasoning, 256K context, and multimodal input to Bedrock's managed infrastructure.
Develop PySpark interactively in VS Code or Jupyter against serverless Spark—no cluster management, with per-session cost tracking.
One click now turns any Cost Explorer report into an AI-generated cost narrative—no manual digging required, at no extra charge.
Data engineers can now run EMR Serverless Spark jobs directly in SageMaker notebooks, with VPC support, AI codegen, and ~30-second warm starts.
Frontier autonomous AI hit a regulatory wall — Fable 5's landmark launch and sudden government-ordered suspension reshapes enterprise AI risk calculus.
MGN gains an AI agent that automates discovery, wave planning, and network setup—cutting manual effort for large-scale cloud migrations.
Amazon Q now explains *why* your costs spiked — pinpointing the API calls and IAM principals responsible — in minutes, not hours.
AI-powered TCO modeling for RDS SQL Server migrations now quantifies licensing, Savings Plans, and MAP credits in one place.
AI coding agents can now switch AWS accounts per request in one session — no restarts, no credential swaps, no wrong-account risk.
Drop into a live coding agent's microVM with a full PTY terminal — debug, inspect, and interact in real time with persistent shell state and reconnect support.
One command now installs and governs AI coding agents across AWS—with live API access, curated skills, and enterprise audit controls built in.
Drop-in OpenAI/Anthropic SDK compatibility meets enterprise AWS controls—with auto-populated code snippets ready to run instantly.
Ask "What data do I have on customer churn?" and get accurate SQL/Python code—no more deciphering cryptic table names.
Data analysts can now resume prior AI-assisted sessions without rebuilding context, saving time across complex, multi-session analytical workflows.
Schedule, parameterize, and chain notebooks into production pipelines natively—no external orchestration tools or DevOps handoffs required.
Embed AI agent reasoning directly into Step Functions workflows—with full audit trails, human approvals, and zero infrastructure to manage.
Government and regulated-industry teams can now run GPT-5.4 agentic workloads inside the GovCloud compliance boundary with full AWS security controls.
Global teams can now use SageMaker Unified Studio in 12 languages — boosting productivity for non-English-speaking data and ML practitioners.
Fine-tune smaller, cheaper models for complex agentic tasks using serverless multi-turn RL — no RL infrastructure expertise required.
AWS Config now tracks Bedrock, AgentCore, and SageMaker resources — bringing compliance and drift detection to your AI/ML infrastructure.
Run Trainium and Inferentia AI workloads in ECS with zero infrastructure management — AWS now handles patching, scaling, and NeuronCore allocation automatically.
SageMaker Studio now provisions in under 20 seconds with fine-tuning and Bedrock deployment permissions pre-configured — no IAM setup required.
Bring your own KMS keys to Quick Research for full encryption control, 15-minute key revocation, and audit-ready CloudTrail logging.
Enterprises blocked by SCP guardrails can now adopt SageMaker Unified Studio without compromising IAM governance — boundaries apply automatically to every new project.
Enterprises can now enforce CMK encryption, custom tags, and rotation policies on AgentCore secrets by managing them directly in Secrets Manager.
Scale HyperPod clusters further by eliminating per-interface IP address consumption — deploy more nodes without VPC subnet exhaustion.
Diagnose GPU faults and NCCL failures on HyperPod clusters in plain English—no manual node-hopping required.
Monitor token usage, error rates, and inference volume for OpenAI/Anthropic-compatible Bedrock workloads with new CloudWatch metrics.
Enterprise teams can now connect Quick's AI assistant to private, VPC-hosted MCP servers—no public internet exposure required.
Skip custom AMI builds — AWS now maintains a production-ready GPU AMI with EFA, Slurm, and PCS Agent pre-validated for instant cluster deployment.
Run OpenAI's GPT-5.5 and Codex inside AWS with IAM, KMS, and PrivateLink—at the same price as going direct to OpenAI.
Anthropic's most capable model yet brings production-ready agentic coding and autonomous task execution to AWS with flexible data residency options.
NextGen OpenSearch Serverless scales 20x faster, hits true zero when idle, and cuts costs up to 60% — built for unpredictable agentic AI workloads.
H100 GPU power comes to SageMaker notebooks—fine-tune LLMs and diffusion models interactively with up to 4x faster performance.
H200 GPUs with 1.7× more memory and 35% lower network latency are now available in SageMaker notebooks for large-scale AI prototyping.
NVIDIA Blackwell B200 GPUs with 1440 GB memory now power SageMaker notebooks in us-east-1 — fine-tune frontier LLMs interactively.
Set a guaranteed node floor before training starts—preventing costly job failures on under-provisioned distributed GPU clusters.
H100-powered P5.48xl instances now available in Tokyo on SageMaker, cutting ML training costs by up to 40% for Asia Pacific users.
P4de's 640GB GPU memory and 60% faster training are now available in Tokyo—cutting costs 20% vs. P4d for large-scale ML workloads.
Track and manage bedrock-mantle token quotas in Service Quotas — critical for teams migrating OpenAI/Anthropic apps to Bedrock at scale.
Broadcasters can now auto-caption live streams in 6 languages with no third-party tools—and save more by bundling it with other AI video features.
Chat your way through Aurora MySQL cluster setup, schema design, and RDS migrations—no SQL syntax or AWS API expertise required.
22 new NKI kernels, Trn3 FP8 support, AI-driven model porting, and Kubernetes topology-aware scheduling land in one release.
IDC-based domain admins can now manage projects, roles, VPC settings, and cross-account access directly inside SageMaker Unified Studio—no AWS console required.
Build a full cloud migration business case in minutes using your existing inventory data, with what-if scenarios and Cloud Value Framework insights.
IAM-based domain users can now catalog, govern, and request access to data assets with AI-assisted metadata—all inside SageMaker Unified Studio.
Manage ML features visually in SageMaker Unified Studio — no API calls needed, with instant cross-tool sync via IAM role.
Swap one URL and your OpenAI SDK calls run on your own GPU instances inside your VPC — no rewrites, no SigV4, full control.
Glue job failures from subnet exhaustion or AZ outages now auto-retry on healthy subnets—no engineer intervention needed.
Bring your own KMS keys to Quick Research for full encryption control, rapid key revocation, and audit-ready compliance in regulated environments.
Native inference traffic logging across three pipeline tiers — no custom pipelines needed, with direct hooks into Model Monitor and fine-tuning.
Tag any Bedrock inference call with team, env, or experiment labels — no setup needed, just add a header and query your logs.
Define and enforce data quality rules on catalog tables and ETL pipelines directly in SageMaker Unified Studio — no separate Glue console needed.
Instant network modernization and CIDR conflict detection before provisioning replaces days of manual review in VMware migrations.
Reserve scarce GPUs for JupyterLab and Code Editor at up to 65% off On-Demand — predictable capacity, prepaid simplicity.
Partner sales teams can now log co-sell deals via chat or document upload — skipping forms and getting AI-driven quality coaching before submission.
Automate prompt tuning and compare up to 5 models at once — with scores, cost, and latency — cutting migration effort from weeks to minutes.
Fine-tune Qwen3.6 27B on SageMaker AI with zero infrastructure management — serverless SFT and RFT now available in four regions.
Bring AWS migration automation into Kiro, Cursor, Claude, or Codex — start, monitor, and complete transformations without leaving your IDE.
Partners and customers can now build and publish custom modernization agents that plug directly into AWS Transform's agentic AI platform via the Kiro marketplace.
Enterprises can now store Transform migration artifacts in their own S3 buckets with custom KMS encryption, unlocking compliance for regulated industries.
Deploy compact image generation and 100+ language embeddings on SageMaker JumpStart in clicks—no heavy GPU or MLOps expertise required.
Deploy multilingual voice cloning, expressive TTS, and 52-language ASR on SageMaker in minutes — no infrastructure setup required.
Two specialized models for agentic coding and efficient reasoning are now one click away in SageMaker JumpStart — covering edge to enterprise.
.NET developers can now modernize apps step-by-step with AI directly in Visual Studio — with full control, checkpointing, and no console switching.
Data Agent now works in enterprise IAM Identity Center domains—letting analysts generate SQL/Python and debug code using plain English.
Fine-grained Lake Formation access controls and Iceberg storage tuning now available directly in the SageMaker Feature Store SDK—no separate tools needed.
NVIDIA H100-powered P5.48xlarge notebooks now available in 7 new regions, cutting training costs 40% and speeding up LLM workloads 4x.
NVIDIA L4 GPU notebooks with 2x faster inference are now available in 9 new Asia Pacific and European regions on SageMaker.
G6e's 48 GB-per-GPU power is now available in 6 new regions, letting you fine-tune 13B LLMs locally without data residency compromises.
G6 instances with NVIDIA L4 GPUs — 2x faster inference than G4dn — now available in Dubai and Malaysia on SageMaker Studio.
P4de's 640GB GPU memory and 60% faster training now reach Tokyo, Singapore, and Frankfurt—at 20% lower cost than P4d.
Access Anthropic's full Claude Platform—including beta agents and tools—directly through your AWS account, with unified billing and CloudTrail logging.
AWS Transform now containerizes your apps during migration—generating Dockerfiles, IaC, and Helm charts automatically, so modernization happens alongside the move.
NVIDIA Blackwell B200 GPUs with 1,440 GB memory now available in SageMaker Studio notebooks—2x faster than P5en for LLM fine-tuning.
New in-product tutorials let you run SQL, build ETL pipelines, and train ML models in under 10 minutes—no setup required.
H100 GPUs are now available in SageMaker Studio notebooks, cutting training costs 40% and speeding up LLM and diffusion model work 4x.
Query Athena data across AWS accounts via IAM role chaining — no data copying needed, with costs billed to the data-owning account.
Simplify user access control and SSO setup while maintaining security across your ML teams with unified administration.
Speed up your Slurm cluster deployment with pre-configured AMIs, eliminating manual setup scripts and reducing time to run AI/ML workloads.
Enable your AI agents to autonomously complete transactions across APIs and services without building custom payment infrastructure.
Keep your OpenSearch data private by routing outbound connections directly through your VPC instead of the public internet.
Enable your AI agents to seamlessly access and share persistent data from S3 and EFS without custom code or infrastructure overhead.
AI agents can now tag and filter long-term memories using structured metadata, enabling more precise and accurate information retrieval.
Unlock 40+ pre-built skills and managed tools to let AI agents autonomously build, deploy, and manage AWS infrastructure with confidence.
AI coding agents can now securely access and manage your AWS infrastructure through a production-ready, cost-free integration layer.
Unlock faster AI workloads and advanced search capabilities with Valkey 9.0's 40% throughput boost and built-in vector+text search—at no extra cost.
Unlock automation for legacy apps that lack APIs by letting AI agents interact with desktop UIs like humans do.
Investigate incidents faster without switching tools—get instant alerts, logs, and root cause analysis directly in your AI assistant.
Government agencies and regulated enterprises can now build and deploy production-ready AI agents in a compliant, fully managed environment.
Troubleshoot AWS issues faster on mobile with AI-powered log analysis and voice search—no extra cost.
Save 95% on processing time by matching only new records instead of reprocessing your entire dataset.
Deploy cutting-edge Qwen models instantly—from edge-friendly compact versions to advanced multimodal reasoning—without infrastructure setup.
Turn hours of dashboard building into minutes by simply describing what you want in plain English.
Ask your data anything in plain English and get instant answers without building dashboards or writing SQL queries.
Save hours on email management with AI-powered summaries, scheduling, and drafting built directly into Outlook.
Fine-tune custom AI models in days instead of months using natural language commands through your favorite coding assistant.
Query Apache Iceberg lakehouse data directly in Amazon Quick—no warehouse needed—with real-time SaaS and streaming data via Zero-ETL.
Build and deploy AI agents in South America with full feature parity—no more waiting for regional availability.
Enable AI agents to automate SAP business processes like order management and finance operations without custom integration code.
Automatically scale your ML inference across instance types without downtime or manual intervention when capacity runs out.
Agents can now securely access downstream resources on behalf of users without requiring separate permission flows for each resource.
Build custom AI kernels faster using natural language agents instead of manual coding on Trainium hardware.
Systematically identify and fix AI agent performance issues with data-driven recommendations, evaluations, and A/B testing—no guesswork required.
Deploy specialized models for multilingual text, document table detection, and European language generation with one click in SageMaker.
Deploy Google DeepMind's latest multimodal AI models with advanced reasoning, function calling, and 140+ language support directly from SageMaker.
Government agencies and enterprises can now access cutting-edge open-weight models from OpenAI and NVIDIA in secure AWS GovCloud regions through a ...
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