Inference cost audit
Price the models you actually run, including input, cache, output, context, and provider markups. Find where the bill is hiding.
AI-native services
Local AI, audited properly.
We map inference costs, test providers, and build local AI systems for teams that need evidence, not vendor slides.
Audit output Evidence-backed
Workload1M in + 250K out
Input costVerified
Cache pricePublished
Provider fitShortlisted
HostingLocal option
A defensible rate card, not a vendor quote.
What we do
Three ways we help.
Provider selection
Compare ownership, hosting, latency, KYC, data posture, and frontier pricing. Pick the provider that fits the workload.
Local AI deployment
Design and ship an OpenAI-compatible local stack: model choice, GPU sizing, caching, evals, and a cost model you can defend.
How it works
Evidence first. Then a decision.
Scope
We define the workload, constraints, budget, and the decision you need to make.
Test
We price and test the shortlisted models and providers against the same workload.
Report
You get a sourced recommendation, a cost model, and the tradeoffs in plain language.
Start here
Request a local AI audit.
Tell us what you are building, which models or providers you are considering, and the budget or hosting constraints. We will reply by email.