More useful AI.
Within your resources.
Longer contexts, uneven expert loads or an ill-fitting kernel can limit useful serving capacity. Fixing one component can simply move the bottleneck elsewhere.
Run AI more efficiently
Serve the workload your team needs, within its memory, latency and quality requirements. Start with the bottleneck—not a shopping list of components.
More useful AI.
Evaluate the relevant placement, compression, routing and kernel changes on the same workload. Choose the supported combination that meets the agreed quality and performance target.
WHAT YOU RECEIVEA useful delivery.
A useful delivery.
Not just an algorithm.
A workload profile and accepted baseline
The selected configuration or implementation
Quality, memory and end-to-end performance comparisons
A defined integration and handover scope
A longer-context serving workload
A team wants to retain more useful context without buying capacity before understanding its bottleneck. SpinForge can assess placement, cache representation and movement, then evaluate the appropriate configuration in the supported serving environment.
Your supported model and serving stack, representative requests, available hardware, and the quality and latency limits you must preserve.
WHAT WE EVALUATEUseful concurrency, accepted model quality, tail latency, throughput, and total execution and data-movement cost.
A larger cache or faster kernel alone is not proof of a better serving service. Combined performance is evaluated on your workload. Infrastructure and operated service responsibilities are agreed separately.
CHOOSE HOW TO WORKUse the software.
Use the software.
Or commission the work.
Software for your team
Choose an evaluation or a qualified production workflow. Compatible methods and shared checks inside its activation scope are included once. Infrastructure is separate.
See plans and deployment scopeSpinForge does the work
Agree the baseline, deliverables, effort and acceptance before implementation. Request managed operation only when it is part of the desired scope.
Discuss an engagementProducts for this workflow +
These are relevant capabilities to evaluate—not mandatory purchases or an assertion that every combination is already integrated.
SpinMemOptimal data-placement software for memory-bound LLM inference across L2, HBM, CXL and NVMe.↗SpinCacheKV-cache compression and direct-decode software for supported long-context LLM serving.↗KX MemoryForgeA multi-tier LLM KV-cache runtime for compressing, offloading and restoring cache in a supported memory and storage environment.↗SpinRouteQUBO-based inference routing for supported cache-locality and mixture-of-experts load-balancing workflows.↗SpinKernelGPU kernel optimization as a QUBO, with supported configuration selection and code generation.↗SpinProofAI-performance assessment software that profiles a workload, prioritizes optimization changes and checks their effect on model quality.↗Token FactoryGPU-fleet scheduling formulated as a QUBO to maximize tokens per watt.↗
Browse the complete catalog Specialist workflows and technical detail +
Bring the problem.
Start with what matters.
Tell us what needs to improve, what you use today and which requirements cannot change.