Trace all your LLM costs
Reduce AI bill
by 30-50%
Your invoice is one number. Your spend is ten thousand decisions. We trace every one.
Read-only. Five days. No savings, no bill.
How it works
The Map.The Cut.The Proof.
01 — The Map
Every dollar gets an owner
We trace spend by model, team and workload, then put the savings figure in writing.
Week one · read-only
02 — The Cut
Your engineers ship the diffs
Routing, caching and batching, each one validated against your eval before it ships.
Thirty days · your deploys
03 — The Proof
Before and after, in dollars
Documented before and after savings, in dollars, every month.
Ongoing · monthly
Proof
Real savings
“Putting this into practice has cut our AI spend nearly in half, while our token usage continues to grow.”
5% → 60%
Coinbase's cache hit rate, after making every request cache-aware.
“Gisting compresses context into a set of learned tokens, preserving its quality while making the model faster and cheaper.”
“The goal isn't to suppress usage. It's to build the infrastructure that makes exponential growth sustainable.”
5× cheaper
Checkr, at 90% accuracy, after moving one high-volume task off GPT-4.
40-60%
Lower per-inference cost at enterprises with mature AI cost governance.
Read-only. Always.
Read access from start to finish. Production is never touched.
No savings, no bill.
The audit costs nothing if it doesn't find 3× its fee in annual savings.
Next step
Cut the bill this month.
It climbs every month, it's spread across four teams, and nobody can tell you why.
Read-only. Five days. No savings, no bill.