AI Spend Console by Rippling - Track your AI spend and connect it to business outcomes
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AI Spend Console gives Finance and Engineering leaders one place to track AI spend across tools (such as Claude and Cursor) and connect it to business outcomes. Break costs down by vendor, model, or employee, then connect spend to GitHub output data like pull request volume and the # of code revisions. You can get started for free–no Rippling subscription required.
Replies
The interesting thing about AI Spend Console is that it goes beyond “who spent what.” AI tools spread fast across teams, and the real challenge is tying usage, ownership, approvals, and ROI back to the org. Rippling has a natural advantage here because the employee, app, and spend context is already connected.
@david_gomez19 you get it!! It’s context built in so you can understand usage and ROI
This is amazing, nice work Rippling team! Quite literally yesterday I asked Codex to build me a better bill tracker / spend tracker to minimize and negotiate for me, so this comes at the perfect time!! Will reach out to my rep!
@mrsharma Thank you so much for the support! Excited for you to try it out, especially given the timing.
Amazing! What use cases do you want to test next?
@vanessa_kahkesh1 I’m definitely interested in bringing more business metrics like JIRA tickets resolved.
Congrats on the launch!
@mcarmonas Thank you for the support!
Congrats on the launch, this sounds like a huge help for finance leaders!
@lina_27 Thanks Lina! Appreciate the support
So this lets you compare individual members of your team on something like (making this up) cost-per-code-revision?
@yash_sathe Hey! You can definitely look at individual usage and spend and compare that to others. You can also look at spend on a role, department, or team.
Congrats on the launch! Can we export the AI spend data directly into our main reporting workflows?
@shreya_barman1 Thanks! You can export the data. You can also share it with your team.
Love this. I think AI spend visibility is step one. The number I ultimately want is contribution profit per workflow/customer after AI cost. Knowing where tokens went is useful. Knowing which tokens actually made money changes the business.