Cost
Met on one workload- Goal
- More than 95% below the direct bill, on every workload.
- Today
- 97.4% below on support tickets, confirmed on fresh cases. Not yet on banking intents, where the cheap route answered differently.
The vision
The default layer for AI spend.
Every AI request, on the cheapest model that answers it exactly as well. Proven on your traffic, receipted to the cent, and never at the cost of a worse answer or your data.
Why this matters
AI spend is set by defaults, not by evidence
Within one provider, the most expensive model costs 100 times the cheapest. Teams pick the strongest model once and send everything to it, because testing a cheaper one on every kind of request is slow and risky. Gimbix turns that test into infrastructure: it runs continuously, on your own traffic, and refuses any change that makes an answer worse.
Six targets
Where each one stands today
Speed
In progress- Goal
- 10 to 30 times faster across a full workload.
- Today
- 94× on repeated requests served from cache and 2.7× on batches spread across providers. Single new requests are about even (1,644 vs 1,651 ms).
Quality
Equal, not yet better- Goal
- Better answers than the model you use today, never worse.
- Today
- On the confirmed route, 142 vs 141 correct and 0 answers made worse. Routes that made answers worse, like the banking ones, were refused.
Privacy
In progress- Goal
- Prompts never leave infrastructure you control.
- Today
- Receipts and evidence carry counts and digests, never prompt text. An open model has served the full banking test from our own server on Oracle Cloud.
Setup
Machine path met- Goal
- From zero to optimized traffic in under ten minutes.
- Today
- 3.5 seconds of machine time from a new key to the first optimized request. The human steps are not timed yet.
Breadth
In progress- Goal
- Every major model, each with its own proof.
- Today
- 345 models priced every day, 22 measured on real customer messages.
Roadmap
From proof to default
- Now
Prove the method in public
Pre-registered benchmarks, published with their failures, on synthetic and real customer traffic.
- Next
Pilots on real traffic
Each customer's own requests prove each route; every saving comes with a receipt their auditor can check.
- Then
A fast lane you own
Open models on dedicated GPUs answer first, without the prompt leaving your infrastructure.
- End state
The default layer for AI spend
Every request on the cheapest model that answers it as well, across every provider, with a receipt.
Principles
What we will not do
- Publish a saving we did not measure, or hide a test that failed.
- Route a request to a model that has not proven itself on that customer's traffic.
- Keep prompt text in logs, evidence or receipts.
- Change the rules of a test after seeing its data.
Evidence
Read the record
The evidence ledger lists every benchmark with its verdict. The BANKING77 page shows 22 models on real customer messages, including the routes that did not pass.