/Docs
jira-cloud
aws-bedrock

Knowledge Indexing - Jira

aiIntermediate

Overview

Extract data from their Jira tickets and turn them into Knowledge articles for a Support use-case by using AI. If you need help reach out in the community in the #ai-help channel! Indexing Jira Project architecture

Set-up

  1. Import the Project into your Tray instance.
  2. Create a Data Table in this Project with the following columns:
  3. Ticket Key
  4. Ticket Link
  5. Decision
  6. Reason
  7. Create a Vector Table in this Project with these configurations:
  8. Name: Something that suits your use-case
  9. Dimensions: 1024
  10. Metric: Cosine
  11. Note: The Embedding Model this Project uses is the Amazon Titan Embedding Text v2 via AWS Bedrock.
  12. Open the Jira extract workflow and configure the Config variables:
  13. jql_to_query_tickets: Define your query to select tickets that will be audited by AI and potentially converted to knowledge articles
  14. Open the Jira Audit + KB Creation + Vector Table Push workflow and configure these steps:
  15. data-tables-1: Select the Data Table created in Step 2
  16. Ensure columns are in this order:
  17. Ticket Key
  18. Ticket Link
  19. Decision
  20. Reason
  21. vector-tables-1: Select the Vector Table created in Step 3

Next Steps

Pair this with our Slackbot and other AI Agent templates to compose your first enterprise Agent. If you need help reach out in the community in the #ai-help channel!