Amazon Web Services

AWS has released support for custom Model Context Protocol (MCP) proxies on Amazon Bedrock AgentCore Runtime, allowing organizations to implement custom governance and security controls on AI agent tool interactions without modifying upstream MCP servers. The serverless proxy runs on AgentCore Runtime with automatic scaling and built-in observability through CloudWatch and OpenTelemetry.

AWS has added OpenAI's latest models, Codex, and a new managed agents service to its Bedrock platform, one day after OpenAI revised its agreement with Microsoft. The integration follows OpenAI's up-to-$50 billion deal with Amazon.

Amazon Web Services released technical guidance for migrating text agents to voice assistants using Amazon Nova 2 Sonic, a native speech-to-speech model that combines automatic speech recognition, reasoning, tool calling, and text-to-speech in a single bidirectional streaming interface. The model supports asynchronous tool calling and built-in voice activity detection for handling interruptions.

Amazon has released a desktop version of its Quick AI assistant that integrates with Google Workspace, Microsoft 365, Zoom, and Salesforce, storing persistent context about user activities to automate tasks. The company also split Amazon Connect into four vertical-specific products: Connect Decisions, Connect Talent, Connect Health, and Connect Customer AI.

Amazon has released Bedrock AgentCore, a platform for building and deploying AI agents with microVM isolation for secure session handling. The platform integrates with Amazon Nova 2 Sonic, a speech-to-speech foundation model, and supports the Model Context Protocol (MCP) for connecting agents to backend services.

Amazon Web Services released a model distillation pipeline on Amazon Bedrock that transfers video search routing intelligence from Nova Premier to Nova Micro. According to AWS, the approach reduces inference cost by over 95% and latency by 50% compared to using Claude Haiku for intent routing.

Amazon released Nova Multimodal Embeddings on Amazon Bedrock, a unified embedding model that processes text, documents, images, video, and audio into a shared 1024-dimensional semantic vector space. The model supports up to 30 seconds of video per embedding and enables semantic search across all modalities simultaneously without converting video to text first.

Amazon Web Services published a practical guide for fine-tuning Amazon Nova models using the Nova Forge SDK's data mixing capabilities. According to AWS, blending customer data with Amazon-curated datasets preserved near-baseline MMLU scores while delivering a 12-point F1 improvement on a Voice of Customer classification task spanning 1,420 leaf categories.

AWS has enabled fine-tuned Amazon Nova Micro models to run on Bedrock's on-demand inference for text-to-SQL generation. According to AWS testing, a sample workload of 22,000 queries per month costs $0.80 monthly using the serverless approach, compared to higher costs with persistent model hosting. The solution uses LoRA fine-tuning on the sql-create-context dataset containing over 78,000 SQL examples.

AWS has released Automated Reasoning checks in Amazon Bedrock Guardrails, a feature that uses formal mathematical verification to validate AI outputs against defined rules. Unlike LLM-as-a-judge approaches that use one probabilistic model to validate another, Automated Reasoning provides mathematically proven, auditable compliance evidence for regulated industries.

Amazon Bedrock has formalized its model lifecycle management with three states—Active, Legacy, and End-of-Life—guaranteeing at least 12 months of availability after launch and 6 months in Legacy status before deprecation. For models with EOL dates after February 1, 2026, a new extended access phase provides an additional 3+ months of access during Legacy state, giving customers more time to migrate applications.

Amazon has introduced stateful MCP client capabilities on Bedrock AgentCore Runtime, enabling agents to pause mid-execution for user input, request LLM-generated content, and stream real-time progress updates. The update transforms one-way tool execution into bidirectional conversations between MCP servers and clients, supporting interactive workflows previously impossible with stateless implementations.

Amazon Bedrock now enables fine-tuning of Amazon Nova models using supervised fine-tuning (SFT), reinforcement fine-tuning (RFT), and model distillation. The service automates infrastructure provisioning and training orchestration, requiring only data upload to S3 and a single API call. Fine-tuned models run on-demand at standard inference pricing without provisioned capacity requirements.

Amazon Nova Multimodal Embeddings, announced October 28, 2025, now supports audio content for semantic search alongside text, images, and video. The model offers four embedding dimension options (3,072, 1,024, 384, 256) and uses Matryoshka Representation Learning to balance accuracy with storage efficiency.

Amazon Bedrock now supports Reinforcement Fine-Tuning (RFT) for customizing Amazon Nova and open source models using reward signals instead of labeled datasets. AWS reports up to 66% accuracy improvements over base models with reduced customization complexity. The approach works best for tasks with verifiable correctness (code, math) or subjective evaluation (moderation, summarization).

Amazon has published a technical guide for building real-time conversational podcasts using Amazon Nova 2 Sonic, its speech understanding and generation model. The solution demonstrates streaming audio generation, multi-turn dialogue between AI hosts, and stage-aware content filtering through a web interface.

Amazon Bedrock AgentCore Runtime now offers managed session storage to persist agent filesystem state across stop/resume cycles and InvokeAgentRuntimeCommand for executing shell commands directly within agent microVMs. The features address two core challenges in production agent workflows: ephemeral filesystems that reset between sessions and the inability to execute deterministic operations without routing them through LLMs.

Amazon Web Services has detailed how its Nova Act browser automation SDK can streamline competitive price intelligence workflows. The service enables developers to build agents that navigate websites, extract pricing data using natural language instructions, and run parallel monitoring across multiple competitor sites—addressing manual processes that consume hours daily and delay pricing decisions.

Amazon Bedrock AgentCore Evaluations, a fully managed service for assessing AI agent performance, is now generally available following its public preview debut at AWS re:Invent 2025. The service addresses the core challenge that LLMs are non-deterministic—the same user query can produce different tool selections and outputs across runs—making traditional single-pass testing inadequate for reliable agent deployment.

AWS has released QA Studio, a reference solution for QA automation built on Amazon Nova Act that enables teams to define tests in natural language rather than code. The system uses visual understanding to navigate applications like users do, automatically adapting to UI changes and eliminating maintenance overhead from traditional selector-based testing frameworks.