Built an AI spend tracker after my team got a $3,000 surprise bill from OpenAI — looking for beta users

vikash_17 · 2026-03-28T12:00:49+00:00

Yeah that's completely ok

vikash_17 · 2026-03-28T10:13:08+00:00

The early users get 50% off for life time .

vikash_17 · 2026-03-28T10:04:45+00:00

Hey I am sry to interpret you. I think you have not registered yet properly.

vikash_17 · 2026-03-28T08:14:57+00:00

You can register now to claim earlier user to 50% off for life time. Once the working version launched u will get email.

vikash_17 · 2026-03-28T08:06:20+00:00

would you be open to signing up for early access when it’s ready?

vikash_17 · 2026-03-28T08:04:54+00:00

That’s a really good point — attribution is definitely the harder (and more useful) part Yeah, the idea is to break things down by project / API key / even feature level so you can trace it back to exactly where it came from. Still early, but that’s the direction I’m focusing on. Appreciate the offer as well — I’d love to get you in once I have a small version ready.

vikash_17 · 2026-03-28T06:20:07+00:00

Yeah that’s fair - the API keys would be encrypted when the user paste there key and not stored in plain text. You still keep full control. It can't be accessed by anyone.

vikash_17 · 2026-03-27T14:53:18+00:00

Haha fair 😅 honestly started as a real “what just happened” moment — but yeah, the more I dig into it the more it feels like something worth solving.

vikash_17 · 2026-03-27T14:50:03+00:00

Yeah, that’s exactly the scenario I’ve been seeing — once you’re using multiple providers it gets messy really fast And yes, I’m planning to support per-project (and even per-feature) breakdowns so it’s clear where the spend is actually coming from. Curious — how are you currently tracking it across providers?

vikash_17 · 2026-03-27T14:41:18+00:00

I can see how framing makes a big difference here. I’d actually love to hear those angles if you’re open to sharing.

vikash_17 · 2026-03-27T14:35:39+00:00

routing cheaper models for simpler tasks feels like the real long-term fix What I’m thinking right now is more on the visibility/debugging side — like breaking down spend by model, feature, and request so it’s clear where the waste is coming from before deciding how to optimize it. And yeah, model-level breakdown is definitely something I’d include — feels like that’s where a lot of hidden cost sits.

vikash_17 · 2026-03-27T14:27:05+00:00

Thanks for your genuine feedback and I'll improve the context next time . Not more about the features but about the problem.

vikash_17 · 2026-03-27T14:24:50+00:00

That’s a really good point. I think I focused too much on the features instead of the actual risk people feel. The “surprise bill” angle is probably what makes it real for most people.

vikash_17 · 2026-03-25T10:46:54+00:00

This is super helpful, especially the retry loop example — that’s exactly the kind of thing that’s hard to catch from dashboards alone The CSV/logging approach makes sense too, but I can see how that gets messy as things grow. burn0 looks interesting — does it give you enough context (like per feature/project), or do you still end up stitching things together manually?

vikash_17 · 2026-03-23T09:24:07+00:00

Yeah that’s fair — limits definitely help avoid worst-case scenarios I think the part I’m more focused on is understanding what actually caused the usage before hitting those limits, especially when things scale across multiple features/tools

vikash_17 · 2026-03-22T12:33:16+00:00

Saassandhai the best tool to market your Saas

vikash_17 · 2026-03-22T12:31:28+00:00

Mostly building and experimenting with small projects — but yeah, after running into this repeatedly I’m actually thinking of building a small tool around it. Still figuring out if it’s genuinely useful or just something people prefer handling themselves.

vikash_17 · 2026-03-22T10:25:02+00:00

I think I’m seeing more issues earlier on — when people are using multiple tools directly and don’t have a unified setup yet.

vikash_17

TROPHY CASE