Race Ready - Rovo assisted power house

Strategy - Plan - Analyze - Find the time - Race Director at Williams Racing to make the best for 2026 season with this 🏎️🏁

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Inspiration

I have been watching F1 from 2016 and I always wanted to know how the F1 team prepares for a race week. The idea was simple, If I'm the race director, how can I leverage Rovo, Jira Service management and other Atlassian ecosystem tools to make the best strategy to win the race. As a race director, I wanted a simple place to manage and strategize for the upcoming season with the help of Rovo and the power of Rovo agent actions. Presenting you Race Ready, the one tool you need as a race director to win the next title 🏎️ 🏁

  • Run with Atlassian Rovo ✅
  • For the Racing industry ✅

What it does

Starting with Jira Service Management to create tickets, using the Jira automation to trigger Rovo agent action, using Playbooks from Confluence to get the strategy suggestions.

It helps you manage the entire race week with Atlassian Rovo, from creating the racing strategy for the race week to checking the race schedule from the F1 official webpage. all while having the human in the loop for finding AI errors 😉

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Below are few of things that this tool can help you with,

  • Get strategy suggestions for a specific track based on weather and track conditions
  • Get the weather information for a specific location of the race
  • Get the track details for a specific race location
  • Get the track schedule for a specific race location
  • Get the driver details for a specific driver
  • Compare the results of two drivers on a specific track
  • Compare the results of a driver from previous races
  • Get the best driver for a specific track based on historical data.
  • Get race predictions based on current weather forecast from get weather action
  • Get previous winners on a specific track

How I built it

I built Race Ready on Forge along with Rovo, and it runs entirely on Atlassian systems. Using the power of Atlassian Rovo, rovo agent actions, Jira service management, and Jira automation, the app read issue fields and goes through the Confluence playbook to match them against the right track strategy. Connecting Rovo agent actions with Jira automation to suggest the necessary information in the Jira panel for the race director to review and validate.

Ask more questions on Rovo chats, with more than 10+ actions. It will help you to find what you want and make you win.

Below the services used,

  • Azure OpenAI Service - Make Chat Completion API calls
  • Jira Rest API - Access Jira ticket details, race type, race tyre, pit stops and more
  • Weather Rest API - Get the latest information on the track track weather
  • Azure Blob Storage - Retrieve F1 assert (car, tyre, driver images)
  • Confluence Rest API - Access page details (track playbook)
  • Forge App Storage - Store the track suggestion and details from LLM
  • node.js - Building the code for Forge backend

Challenges I ran into

  • The one big challenge is parsing the data from F1 page and fetching the right html tags to get the relevant information before passing it to Azure OpenAI models
  • Making both Rovo and Jira Panel with the same app was different as I kept getting error but the forum was helpful to debug some of it (window not found - this was one of the error which bugged me a lot 😡)

Accomplishments that I'm proud of

  • Connecting and integration of different components together was probably the best of it, when you have two different forge apps running from the same code base with the same manifest.yaml - the dependencies and stuff gets haywire 🥲

  • I have integrated extraction of live information from F1 official race page, call Azure OpenAI models, store information in Key-value store, store images in Azure Blob Storage, making sure the prompt is good enough to make the driver comparison

What's next for Race Ready

The next feature is already on the way, Analyze the driver performance live on the race day, like after every lap share important information. This can be very interesting and challenging as it need real-time or near real-time telemetry data of the car, driver and other teams data.

Let me know what you think about my hack!

Happy Hacking - Sandy! 🤞🏻

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