We evaluate models and AI vendors on the only benchmark that matters — your workload, your data, your risk, and your budget — across OpenAI, Anthropic, Google, and open-weight alike. Chosen on fit, never on vendor allegiance, with lock-in and exit planned before you sign.
New models ship monthly, every vendor's benchmark says they win, and none of it tells you how a model performs on your documents, your terminology, your edge cases, and your compliance boundary. Meanwhile the wrong commitment compounds: pricing shifts, capabilities lag, and the switching cost grows with every workflow you wire in. Model choice is a business decision — it deserves the same discipline as any other vendor of record.
Workload, latency and volume, data sensitivity and residency, integration constraints, budget envelope, and the risk profile your industry demands — the evaluation criteria are set before any vendor demo.
Structured evaluation on your real tasks and documents — capability, consistency, cost per outcome — alongside a security and data-handling review of every candidate: training-use terms, retention, residency, and the contractual guardrails.
A ranked recommendation with the evidence behind it: total cost modeled at your volumes, lock-in exposure named, and an exit path documented — so you sign with eyes open.
The same rigor you'd apply to any strategic vendor — applied to the layer changing faster than any of them.
OpenAI, Anthropic, Google, and open-weight models evaluated identically, on your tasks — selected on client fit, never vendor allegiance.
Training-use terms, retention, residency, tenancy, and certifications reviewed like the vendor risk decision it is — before your data goes anywhere.
Cost per outcome at your real volumes — not list price per token — with sensitivity to growth, so finance sees the bill before it arrives.
Abstraction points, portability, and a documented exit path — so today's right answer doesn't become next year's hostage negotiation.
Engagements run per evaluation or as an annual watch. Pricing scales with the candidates and workloads in scope, not the size of your team.
For teams that need a defensible model choice for a specific system.
For enterprise commitments where security and exit terms matter as much as capability.
For organizations that want the model landscape watched, not rediscovered annually.
Pricing scales with the candidates and workloads in scope. Book a scoping call and we'll scope the evaluation and give you a real number.
Cream City Cyber is honored to stand among the businesses powering Milwaukee's growth — proof that world-class security expertise and deep community roots belong together.
