LLMBurner meters every dollar your AI burns — in the products you ship and across your team. One proxy for your code's LLM calls; a desktop app + Chrome extension for everyone else. Every cost, one panel. Currently being built — get in early.
Enterprise LLM spend more than doubled in six months. The teams writing those cheques mostly can't tell you which feature spent what.
Of enterprise AI teams report LLM spend exceeded their first-year projections. Surprise bills are the norm, not the exception.
The cost of equivalent-quality inference drops 10× every year. Teams that don't re-route stay locked to last year's prices — paying multiples for the same answer.
To meter your product's own LLM calls — one base URL, no SDK swap, no middleware. For your team's AI spend, the desktop app + Chrome extension are coming.
I was shipping a small AI product — a Claude wrapper, the kind every indie builder ships these days. Every user request hit the API. Every reply ate tokens. And every month the bill arrived without telling me which feature, which user, or which prompt ate the most.
I looked for a tool that would just meter the calls and tell me where the money was going. What I found was either an enterprise observability suite priced for Series B, or a logging library I'd have to wire into every SDK. Nothing in between. Nothing for someone who just wanted to see the bill, route the cheap calls to a cheap model, and cap the budget before something runs away overnight.
So I'm building it. Solo, on AWS, in public. If you've ever opened an LLM invoice and squinted — I'd love to talk to you before I write the next line of code.
"Reset my password. The link in the email isn't working."| Model | In | Out |
|---|---|---|
| haiku 4.5 | $0.80 | $4.00 −12% |
| gpt-5 nano | $0.05 | $0.40 0% |
| gemini flash | $0.38 | $1.50 −14% |
| llama 3.3 | $0.09 | $0.59 0% |
| sonnet 4.6 | $3.00 | $15.00 0% |
| opus 4.7 | $15.00 | $75.00 — |
I'm before v1. Talk to me for 20 minutes — show me your stack, your worst LLM bill, the feature you wish existed — and your priorities go straight into v1. The first 10 callers get free beta access for life.
Every route, every feature flag, every model — attributed in real time. No more looking at a monthly invoice and guessing which feature caused the spike.
# no visibility # no cost tracking # no alerts from openai import OpenAI client = OpenAI( api_key="sk-...", base_url="https://api.openai.com/v1", )
# every call tracked # costs · tokens · latency # budgets · alerts · routes from openai import OpenAI client = OpenAI( api_key="sk-...", base_url="https://api.llmburner.app/v1", )
Every call, attributed to the route or feature flag it came from. SQL on top if you want it. CSV export if you don't.
live · $/callSame prompt across GPT, Claude, Gemini, Mistral, Groq. Stacked outputs, tokens, latency, cost. Pick the cheapest one that's correct.
8+ providersCap any provider by dollars or requests. When a runaway loop hits the ceiling, the burner stops the burn.
trips < 30sEvery model, every provider, current price. Refreshed when providers push. No more stale spreadsheets.
real-timeFolders per project. Pin the winning system prompt. Diff and roll back when the new one ships a regression.
∞ versions"Route support-bot through Haiku 4.5, save ~42%, no quality drop." A sentence. Not a chart you have to interpret.
weekly digestSpend by machine and by person, not just by route. Desktop app and Chrome usage land in one panel — track a single account across three PCs, or a whole company with many seats, and see exactly which device is burning.
per-device · per-seatI'm not going to fake a green LIVE badge to make this look further along than it is. Here's the real status — built, building, and the two things I'd genuinely like your opinion on.
No. LLMBurner is pre-launch — I'm a solo founder, building v1 right now. The console screenshots above are design previews of where I'm headed. The numbers in them are illustrative, not real customers. If you sign up, you'll get a personal email from me, and the first version when it ships. If that's not what you want, please don't sign up — I'd rather have 30 honest signups than 1,000 strangers.
Helicone and LangSmith are observability-first; OpenRouter is routing-first. LLMBurner combines both in one proxy and gives you a second mode where you can buy tokens through us at a small discount instead of juggling five provider accounts. That managed-tokens mode is the differentiator — nobody else does it that I've seen. If they ship it before me, I'll tell you here honestly.
No. LLMBurner will be a hosted proxy on AWS. You change one base URL in your existing OpenAI/Anthropic SDK. No library to install, no service mesh, no agents. Point the URL back to the provider any time you want — there is no lock-in either way.
The plan: we don't train on your data, ever. By default we'd log sizes, tokens, latency, timestamps — not prompt or response bodies. Body logging will be opt-in per project, encrypted at rest. I'd rather lock this down right than ship it loose, so if you have strong opinions on the privacy model, that's another thing worth a call.
Free during beta. After that, two modes: BYOK = flat per tracked request, well below what the meter saves you. Managed tokens = provider rate plus a disclosed margin, with a starting discount on first topup. If it doesn't save you more than it costs, don't pay me.
Plan is to deploy in the same regions as the providers. Target added latency <15ms p50. I'll publish the real number on a public status page once v1 is live — not before, because measuring an unbuilt thing is exactly the kind of fake number I'm trying to avoid putting on this page.
I'm Krupesh — solo developer, building in public. krupesh.dev. I'm building this because I ran into the problem myself on a small Claude-wrapper project. I personally read and reply to every waitlist signup. If you book a call, you'll be talking to me, not a salesperson — because there are no salespeople.
Drop your email. You'll get a personal note from me, an honest update when v1 ships, and the chance to shape what gets built first. No drip campaign. No newsletter. Just real signal.