Run AI on your terms.

FuZeCORE

Right-sized private LLM hosting, priced for outcomes

If a team just wants a strong hosted model behind their own perimeter, FuZeCORE is the baseline offering. The differentiation is that customers don't have to guess which model, runtime, or GPU stack they actually need.

• Avoid overpaying: pick the smallest model that clears the use case, then scale only when needed
• Measured selection: we benchmark runtime stacks (Ollama, llama.cpp, vLLM, Triton, etc.) on the target hardware class
• FuZe optimizations: run benchmarks with and without system/CUDA tuning so you're buying the best-performing configuration
• Future-proof: swap models later as requirements change, without re-buying the platform

FuZeADMIN

Customer-visible control plane, no model lock-in

Customers get access to FuZeADMIN inside their own trust boundary to manage nodes, models, benchmarks, and deployments. FuZeADMIN ships with a tiered, curated model catalog per hardware class (with footprint + runtime-compatibility metadata, and optional artifact digests/signature verification) so teams can install candidates, test in pre-production, and promote to production with controlled rollout and rollback. As needs change, operators can swap models, pin versions, or run multiple models side-by-side on the same appliance or across a fleet. Scaling is additive: attach FuZeBOX workers or provision FuZeCLOUD nodes, and FuZeADMIN helps place models across the fleet without forcing a single model choice.

Sample: one node benchmarked across baseline vs FuZe-optimized runtime. The platform selects the best winning combination for the customer's hardware and workload suite.