I want to know what my customer wants! And I want to automate it. I tried “classical” NLU and “modern” LLM - but we do not understand 100% of the queries. How to achieve that? Well, there is a third twin. Let’s have a look how we achieved 100% correctness with the HelloFresh chatbot intent resolution.
Amazon Connect has some really cool AI features. One of them is the Agent Assist, which allows agents to quickly access relevant information and insights during customer interactions. To adapt the behaviour to your own needs, you can do some prompt engineering and use your own prompts. And of course we use IAC - infrastructure as code, that means CloudFormation. BUT as the features are so new, the error messages are much to short. So let`s do some detective work. And automation…
The Mailbox challenge: Amazon SES, the simple Email Service, has no mailboxes. What if you want to use it as a mail server and just have a mailbox? Just Build an IMAP Server - Here’s How.
MCP Authentication for Agent Connections in Amazon Bedrock AgentCore: A Complete Guide Agents are currently the go-to topic in AI, with AWS heavily pushing Amazon Bedrock AgentCore as the next-generation platform for building intelligent, tool-enabled applications. However, while LLMs excel at language understanding and generation, they have fundamental limitations in performing complex calculations, data processing, and accessing external systems. While an LLM might have learned that 2+2 equals 4, it cannot perform integral calculations or access real-time data from external APIs.
AWS released GA Automated Reasoning checks for Bedrock. What sounds so small could be the actual drug against AI hallucinations. But it turns out: It is complicated! Let me show you, what I mean.
At the beginning of a AWS software development project, some big architectural decisions need to be made. This is a classic: does AWS Lambda or Docker/Microservice make more sense? Well - with the GOpher Chameleon, you can have both worlds. The very same code for Lambda or container.
Lambda@Edge functions are executed in multiple regions around the world, but which ones exactly? In this post we’ll find out together, which will enable us to pre-create log groups and other resources for them.
Your agentic multi-channel, multi-modal GenAI solution idea may be buzz-word-compatible. But to do some expectation management: It will not run as fast as this dog. So, we share some of the tips from our projects on how to speed up your GenAI solution.
