Artificial Intelligence

Category: Customer Solutions

How Tamnoon built AI-powered cloud security remediation with Amazon Bedrock

How Tamnoon built AI-powered cloud security remediation with Amazon Bedrock

Learn how Tamnoon built Tami, an agentic cloud remediation orchestrator on Amazon Bedrock that autonomously investigates and safely remediates cloud security findings from CNAPP and cloud-native sources. The approach drove a 90%+ reduction in critical cloud exposure in 90 days with zero production issues.

Building agents that transact with Anchor Browser and AgentCore payments

Building agents that transact with Anchor Browser and AgentCore payments

Learn how the AWS Generative AI Innovation Center Partner Agent Factory and Anchor Browser built AI agents that autonomously pay for x402-protected web resources and APIs. Amazon Bedrock AgentCore payments checks budgets, signs transactions, and retries requests without exposing wallet credentials to the agent runtime.

Natural language security queries at Orca Security using Amazon Bedrock

Natural language security queries at Orca Security using Amazon Bedrock

Orca Security built Discovery AI, a natural language query agent on Amazon Bedrock that converts plain-English questions into Sonar queries. The post shares the multi-stage architecture and the results: 90% lower query cost, 93% fewer input tokens, and 75% lower latency than the initial baseline.

How ShipStation Global built an AI IT help desk on Amazon Bedrock AgentCore

How ShipStation Global built an AI IT help desk on Amazon Bedrock AgentCore

ShipStation Global’s engineering team built Deckhand, an AI IT help desk agent for Slack on Amazon Bedrock AgentCore. It answers routine IT questions from a curated knowledge base, reads error-message screenshots, and files Jira tickets. In its first three months it resolved 97.5% of channel queries with a 96% positive feedback rating.

How Postman runs Agent Mode for 40 million developers on Amazon Bedrock

How Postman runs Agent Mode for 40 million developers on Amazon Bedrock

Building an AI agent that works in a demo is a different problem from running one for 40 million developers. Postman and AWS share the architectural patterns behind Agent Mode: controlling tool sprawl, exposing schema-based reads, and treating context as the real bottleneck, plus how it runs on Amazon Bedrock at scale.

Pay-per-inference for AI agents: How BlockRun and Incarna use Amazon Bedrock AgentCore payments

Pay-per-inference for AI agents: How BlockRun and Incarna use Amazon Bedrock AgentCore payments

Amazon Bedrock AgentCore payments gives AI agents a managed way to pay for services on demand, with spending limits enforced by the infrastructure. See how Incarna’s agents pay BlockRun for model inference one request at a time over x402, cutting the work of adding x402 payment support from months to days.

How Cornerstone OnDemand cut database diagnosis by 78% with Amazon Bedrock

How Cornerstone OnDemand cut database diagnosis by 78% with Amazon Bedrock

Cornerstone OnDemand built Orion AI, a multi-agent system on Amazon Bedrock and Strands Agents, to turn database operations from reactive firefighting into proactive automation. A three-person team cut database diagnosis from 45 minutes to 10, a 78% reduction, in six months. See the design decisions other teams can reuse.

Evaluating multi-agent systems for explainability and helpfulness with Amazon Bedrock AgentCore

Evaluating multi-agent systems for explainability and helpfulness with Amazon Bedrock AgentCore

Multi-agent systems need deeper guarantees than fluent responses: they must select the right tools, respect constraints, and explain their decisions. Learn how to build a Strands-based multi-agent supply chain decisioning system and evaluate it with Amazon Bedrock AgentCore Evaluations using built-in, custom, and explainability evaluators.

Uplifting conversion across the acquisition funnel with personalization using contextual bandits on AWS

Uplifting conversion across the acquisition funnel with personalization using contextual bandits on AWS

Generative AI makes it cheap to produce personalized content at scale, but which variation do you show each customer? Amazon Payments used a multi-objective contextual bandit on Amazon SageMaker AI to personalize an acquisition funnel, achieving a high single-digit conversion lift for one audience, and learning why content, not the model, was the constraint.