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AtlasBurn
Know what your AI will cost before the invoice does
AtlasBurn is cost intelligence for AI-native companies. Most tools show what you already spent; AtlasBurn forecasts what you're about to. It models runway and burn probabilistically, attributes spend by model and feature, and applies real-time budget guardrails that stop runaway agents and cost overruns at the edge before the invoice, not after. It treats AI cost as a risk problem, not an accounting one.
Hey Product Hunt, I'm Akhil, and I've been building AtlasBurn.
Every AI-native team I talked to had the same problem: their bill could tell them what they already spent, but nothing told them what they were about to spend as they scaled. You add 10k customers and inference cost doesn't grow 2x, it grows ~3x and nothing "broke" to cause it. You just find out from an invoice.
AtlasBurn treats AI cost as a risk problem, not an accounting one. It ingests your LLM usage and forecasts your burn and runway probabilistically (a distribution, not a single number), attributes spend by model and feature so you know why it's moving, and enforces real-time budget guardrails at the edge that stop runaway agents and overruns before the next provider call.
I'd love feedback from anyone running LLMs in production: what breaks your cost model as you scale, and what would you want a tool like this to catch?
Thanks for checking it out.
About AtlasBurn on Product Hunt
“Know what your AI will cost before the invoice does”
AtlasBurn was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #136 on the daily leaderboard. AtlasBurn is cost intelligence for AI-native companies. Most tools show what you already spent; AtlasBurn forecasts what you're about to. It models runway and burn probabilistically, attributes spend by model and feature, and applies real-time budget guardrails that stop runaway agents and cost overruns at the edge before the invoice, not after. It treats AI cost as a risk problem, not an accounting one.
On the analytics side, AtlasBurn competes within SaaS, Developer Tools and Artificial Intelligence — topics that collectively have 1M followers on Product Hunt. The dashboard above tracks how AtlasBurn performed against the three products that launched closest to it on the same day.
Who hunted AtlasBurn?
AtlasBurn was hunted by Akhil Anand. 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.
For a complete overview of AtlasBurn including community comment highlights and product details, visit the product overview.