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As part of my continued learning of the AWS services (and more recently, the AI services), I began working on an AI powered Slackbot using Amazon Lex linked in with Amazon Kendra, with indexed data from a variety of data sources (Jira, Confluence, Google Drive etc)

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Creating an AWS AI Chatbot

Project: DilBot

Screenshot 2024-10-11 at 07 05 03

Project overview

After completing the AWS AI Practitioner course, I wanted to test my knowledge of the services, and create a chatbot that would be used via Slack.

These are the requirements I went into the project with:

  1. The bot needed created using AWS Services
  2. The bot needed to utilise GenAI for interactive discussions
  3. The bot needed to link in with Slack
  4. As well as GenAI, the bot needed to have access to domain based data
  5. The bot must be easy to use Bonus - If I could get the bot to work via Alexa

After reviewing the options, the following services required greater analysis due to GenAI/ChatBot features, and data indexing:

Amazon Kenda - Kendra at a high level provides indexing via Amazon S3 or via API with large etxternal companies such as Google, Microsoft and Atlassian.

Amazon Lex - Lex is a chatbot that can be configured with custom intents, allowing for a personal end user experience, with the ability to bounce user queries.

Amazon Q - Is a managed subscription based chatbot, allowing for users to interactive with the client within web or mobile UIs.

The next phase will involve a deep dive exploration of the key features, customerisation and cost of each.

Project planning

Evaluation of the AWS AI Services

📝 Note: When exploring these options, it was important to weigh up cost v feature sets 📝

Amazon Lex: Build bots with Conversational AI

Amazon Q: The most capable generative AI–powered assistant for accelerating software development and leveraging companies' internal data

Amazon Kendra: Find answers faster with intelligent enterprise search powered by machine learning

Project design

Project implementation

Project recap

Things I would like to improve

Conclusion

About

As part of my continued learning of the AWS services (and more recently, the AI services), I began working on an AI powered Slackbot using Amazon Lex linked in with Amazon Kendra, with indexed data from a variety of data sources (Jira, Confluence, Google Drive etc)

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