AWS Machine Learning Blog

When an AI agent uses Web Search to ground its answers on behalf of a customer, the organization behind that agent needs domain and date filters to control which sources the agent consults and how fresh those sources must be. A financial-services agent shouldn’t ground its answers in an unvetted blog. A product-information agent shouldn’t cite pricing or inventory data from t...

Mortgage lending runs on documents. Every loan starts with a familiar set: earnings statements, W-2s, bank statements, driver’s licenses, voided checks, and insurance applications. Every lender processes them at scale. The challenge of classifying, extracting, and validating high volumes of documents isn’t unique to mortgage lending. Organizations in banking, insurance, healt...

Asynchronous invocation patterns for Amazon Bedrock AgentCore agents in serverless pipelines remove idle compute costs while your AI agent processes requests. A common example is document validation: in a real-estate financing back office, an agent can read a property record or loan contract, reason about whether the information is complete and consistent, and return a verdic...

Fanatics Betting and Gaming (FBG) built a multi-agent customer support system on AWS to solve a challenge unique to sports betting. Customers expect instant, accurate answers, especially during live events when every minute counts. Customers ask about account issues, deposit limits, state-specific regulations, and responsible gaming resources. The rules vary across every juri...

KnowledgeForge is about mining gold from the IT Service Management (ITSM) ticket graveyard: the resolved incident tickets whose knowledge never reaches a knowledge base article. Enterprise IT support teams resolve thousands of tickets every month, and each one holds ...