This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
Your multi-provider invoices arrive as one number nobody can explain. AI SpendOps is a managed gateway that prices every LLM call as it happens and attributes it to the team, feature or customer that caused it. Unlike tracing tools, it is built for cost accounting, not debugging, and it never stores prompts or responses. Point your SDK at it, add one header, keep your own keys. Budgets with email alerts flag runaway spend early.
Hi Product Hunt, Linsay here, CEO of AI SpendOps.
We built this because we kept seeing the same thing: companies adopting AI quickly, and then being unable to attribute the spend correctly from an accounting point of view.
Every provider gives you a dashboard and one invoice line. None of them knows about your features, your customers or your cost centres, so finance ends up with a single growing number and nobody who can say what is behind it. Three questions come up again and again:
Development vs production. Experimentation and live customer traffic land on the same invoice, but they are not the same kind of cost. One is R&D, the other is a cost of delivering your product, and they need to be accounted for separately.
The true cost of each AI feature against the revenue it earns. If you sell a product with AI inside it, you need the cost per feature and per customer to know your real margin, and whether your biggest customer is also your least profitable one.
Internal AI costs against the KPIs they are meant to improve. Support, sales and operations teams are all adopting AI. Without the cost per team and per use case, nobody can say whether the improvement was worth what it cost.
AI SpendOps is designed to plug in quickly and start adding value straight away. Change three lines: point your existing SDK at our gateway, add one header, keep your own provider keys. There is nothing to host and no data project to run first. From your first call, every request is priced as it happens and attributed to the dimensions you define, such as environment, feature, team, customer or cost centre. It works across 16 providers, including OpenAI, Anthropic, Gemini, OpenRouter and Vercel AI Gateway, so the figures sit in one place however your teams buy their AI. It stores metadata only. Prompts and responses are never stored.
Budgets send email alerts at each warning level, with a burn-rate projection, so you know spend is running away long before the invoice arrives.
The first 2 months are free, so you can see your own numbers before you pay anything.
Which of those three questions is the hardest for your company to answer today? I will be here all day and would love to hear.
Linsay
Been using AISpendOps for a while now at an Insurance Company. The insights we get are incredibly powerful and help us expand our AI rollout in the most efficient way, whilst keeping an eye on cost.
Congrats on the launch!
About AI SpendOps on Product Hunt
“Reduce your AI spend with detailed monitoring”
AI SpendOps was submitted on Product Hunt and earned 9 upvotes and 3 comments, placing #60 on the daily leaderboard. Your multi-provider invoices arrive as one number nobody can explain. AI SpendOps is a managed gateway that prices every LLM call as it happens and attributes it to the team, feature or customer that caused it. Unlike tracing tools, it is built for cost accounting, not debugging, and it never stores prompts or responses. Point your SDK at it, add one header, keep your own keys. Budgets with email alerts flag runaway spend early.
AI SpendOps was featured in Analytics (173.8k followers), Developer Tools (519.9k followers) and Artificial Intelligence (479.2k followers) on Product Hunt. Together, these topics include over 224.6k products, making this a competitive space to launch in.
Who hunted AI SpendOps?
AI SpendOps was hunted by Linsay Stichbury. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how AI SpendOps stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Linsay Stichbury