SuperPenguin
AI spend intelligence for engineering and finance teams
What this is
Tracks and attributes AI usage costs across OpenAI, Anthropic, Gemini, AWS Bedrock and more, so engineering and finance teams can see what's actually driving their AI bill. A cost dashboard, not itself an API product.
Our one-line summary — not the founder’s tagline.
- How it works
- Ingests usage and billing data across an AI stack (OpenAI, Anthropic, Gemini, Deepgram, ElevenLabs, AWS Bedrock and more) and attributes every dollar of spend down to the specific customer, feature, team, model and provider responsible.
- What's different
- Gives per-request cost attribution instead of a single opaque monthly invoice.
- Best for
- Engineering and finance teams whose AI bills are scaling faster than their visibility into them.
What we measured
Nobody else publishes this — it comes from knocking on the door every day.
- Watched by us
- 10 days
- Last checked
- 4d ago
Where it shows up
Every group here is a page of its own — each one checked daily.
The numbersIs it still shipping, is it overpriced, where did it land — and what the price is built from.
League price & chart
No money. No seat. It goes on your record — and in 28 days reality settles it.
Calls are closed while we rebuild accounts. You can still read every one of them.
AI. Launched 10d ago on PeerPush, where it placed #556. Today, it's been quiet for 10 days and the price has started to bleed.
Already bleeding a little every day, and it accelerates the longer it stays quiet.
We check this site every day, ourselves. A founder can post “still working on it” — a claim like that doesn't price. What we price is what we can verify from the outside: evidence, not announcements. The real question isn't “will this be huge?” — it's “will they still be moving in four weeks?”
The market viewHow this launch is priced and ranked in our league — the investor side of the page.
ranked by the reality anchor, not the market price
It placed #556 on PeerPush with 11 votes.
No matter how much money goes in. There is no pump here — you can't make yourself right by buying more. The line only moves on things that actually happened: an award, revenue that grew, a new platform, code that shipped — or silence.
A launch that goes quiet eases down a little at a time — never a cliff you could have run from the night before.
How the launch is moving on its own board, day by day — the crowd's attention.
A flat line is normal: votes stop within a day or two of launch, on every board. What's unusual — and what actually counts — is a launch that keeps pulling votes long after its day is over.
About
SuperPenguin is an AI spend intelligence and cost attribution platform for teams whose AI bills are scaling faster than their ability to understand them. As companies wire LLMs, voice, and other AI services into their products, spend explodes across half a dozen providers with almost no visibility into what is actually driving it. SuperPenguin opens that black box. The platform ingests usage and billing data across your AI stack (OpenAI, Anthropic, Gemini, Deepgram, ElevenLabs, AWS Bedrock, and more) and attributes every dollar down to the specific customer, feature, team, model, and provider responsible for it. Instead of a single opaque invoice at the end of the month, engineering and finance teams get per-request attribution and a clear answer to the question that actually matters: where is our AI money going, and why? What you can do with SuperPenguin: See true cost per customer and per feature. Know which accounts are unprofitable, which features are expensive to run, and how AI cost maps to the revenue it supports. Track ROI on AI tooling. Measure spend on AI coding tools like Cursor against the productivity they deliver, so engineering leaders can justify or right-size their investment with data instead of gut feel. Surface waste and optimization opportunities. Spot runaway spend, inefficient model choices, and requests that could be cached or routed to cheaper models, then act on them. Unify multi-provider spend. One view across LLMs, voice, image, and vector services, rather than logging into each provider's console separately. Give finance and engineering a shared source of truth. Both teams work from the same attributed numbers, which turns AI cost from a monthly surprise into a managed line item. SuperPenguin processes over 100 million API requests and is built for engineering and finance teams at companies where AI spend has crossed the threshold from rounding error to real budget line. Early customers have used it to cut their AI bills. Stop guessing at the black box of AI spend. Start attributing, understanding, and optimizing it.
Where it launched
1 platform| Platform | Votes | Counts toward price | Link |
|---|---|---|---|
| PeerPush | 11 | sets the price | ↗ |
The board it did best on sets the price. Every other board only adds to it if the launch also placed high on that board too — because just showing up somewhere isn't an achievement. Listing on twelve directories is free; placing well on them isn't.
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