Get per-identity Amazon Bedrock cost visibility and enforceable spend limits using only AWS-native features, with no application code for the common case. Attribute spend with IAM principal tags, report with CUR 2.0 or Cost Explorer, and enforce with AWS Budgets actions that a…
Tokenomics at scale: Track and cap Amazon Bedrock spend per IAM principal with CUR 2.0 and AWS Budgets How Constellation is building a governed data foundation on Databricks Constellation operates the largest nuclear fleet in the United States. For them,...
Eclipse Aerospace simplifies flight-data ingestion with Databricks As organizations in aerospace, manufacturing, life sciences, and other data-intensive...
LLMON: An LLM-Native Markup Language, now in Granite 4.1 3B and 8B Optimizing cost per task and proving agent ROI on Amazon Bedrock Comparing per-token prices hides the real cost of running a model on Amazon Bedrock. This post shows how to calculate the true cost per task across four hidden cost drivers, reduce it with caching, routing, and output constraints, and prove agent ROI with human baselines, hold…
Building a self-service LLM gateway with Amazon Bedrock and LiteLLM Build a self-service LLM gateway with LiteLLM on AWS Fargate that puts Amazon Bedrock foundation models behind an OpenAI-compatible API. Developers get instant access through a single API key, while platform teams gain per-user cost controls, quota isolation, and observability.
Introducing Gemini 4 Hydrogen Google Search gets a major upgrade with Gemini 4 Hydrogen We are bringing Gemini 4 Hydrogen to Google Search globally to provide you with more helpful, visual, and intuitive responses.
Run agents securely and efficiently with the next generation AgentCore runtime AI agents now run multi-step workloads for hours and act on behalf of users, raising the bar for secure, scalable agent compute. Learn how the next generation of Amazon Bedrock AgentCore runtime delivers hardware-isolated sessions with faster starts, more compute, usage-based …
How H6.ai builds AI-powered financial automation with Lakebase Postgres Traditional accounts payable and invoice processing tools often force companies into a trade-off...
Lakehouse//RT: Scale real-time analytics, not your bill AI agents are pushing the limits of data warehouses. A human analyst might run a...
Migrate to Amazon Bedrock Managed Knowledge Base with your coding agent The migration guide in the amazon-bedrock skill helps you migrate a customer-managed Amazon Bedrock knowledge base to a Managed Knowledge Base. Your coding agent plans the move with read-only discovery, creates the new knowledge base or an infrastructure-as-code template along…
Anthropic files S-1 with the SEC for proposed initial public offering Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.
Build composable, interoperable multi-agent systems with A2A on AWS Build a composable, interoperable multi-agent system on AWS with the Agent-to-Agent (A2A) protocol. A LangChain orchestrator on Amazon ECS communicates with a Strands agent on Amazon Bedrock AgentCore across organizational boundaries, using bidirectional, OAuth-authenticated c…
Fine-grained access control for Amazon Bedrock Managed Knowledge Base tools Learn how to expose an Amazon Bedrock Managed Knowledge Base to AI agents as MCP tools through Amazon Bedrock AgentCore Gateway while keeping per-user access control. A request interceptor injects verified identity, Policy in AgentCore validates it independently, and a resourc…
From prototype to production: Engineering agents with Agent DLC Agents stall between demo and release when teams lack a repeatable way to measure how good an agent is and whether the last change helped. This post covers three agent properties that break traditional CI/CD, a measured case where an aggregate metric hides a coverage gap, and …