I didn't set out to build a cost tool. I built StackSpend because our own AI bills kept ambushing us. Hey Product Hunt 👋 I'm Andrew. We're a growing AI company, and over the last year our spend got away from us in ways nobody caught until the invoice landed: • A release went out with a bad change and our OpenAI cost spiked overnight. • A Google Cloud account got compromised — someone hammered the Gemini API and ran up ~$9,000 before we noticed. • Google deprecated a Gemini Flash Lite model and migrated our workload onto the newer Flash — about 3x the price for the same calls. • Our engineers adopted Cursor fast. Great for velocity — but some were quietly burning hundreds of dollars a day, each. Every one of these was invisible until the monthly invoice. By then the money was gone and I was reverse-engineering what happened weeks after the fact. We didn't need another dashboard. We needed to track spend across the whole stack, forecast and budget for what our teams would actually burn, and catch anomalies the day they happen — tied to the change that caused them, not discovered a month later. So we built that: 📊 Track every dollar across the AI stack and the cloud it runs on — read-only connect in ~5 min, 90 days backfilled, 14+ providers 📈 Forecast month-end and set budgets, with days-to-risk warnings before you breach 🚨 Catch anomalies same-day — matched to the deploy that likely caused them. The AI reads the diff and points at the suspect change; we flag it as likely and let an engineer confirm. We never assert the cause. 🎯 Spikes become assigned tickets in Linear/Jira — owned, not watched 🤖 Or just ask Signal: "why did we spike on Tuesday?" — answers with the numbers cited Flat pricing from $29/mo, never a % of your bill. Full 14-day trial, no card. Ask me anything — including the messy bits: what we still don't cover, how we avoid blaming the wrong PR, and what that $9k lesson actually cost us.