Workflow-first compression sales motion

This turns model compression from a back end cost saving into a top of funnel sales motion. Luminary lets Multiverse start with the customer’s actual task, run a realistic bake off across models, and prove when a smaller compressed model can hit the same success and compliance target with lower latency and cost. That creates a clean handoff into CompactifAI instead of asking buyers to trust compression claims in the abstract.

• The workflow is concrete. Luminary simulates multi step customer interactions with tool calls and policy checks, then scores candidate models on task completion, compliance, latency, and cost. That matters because enterprises buy for a narrow workflow, not for benchmark averages.
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• CompactifAI has a strong economic hook once that proof exists. Multiverse says compressed models can cut size by up to 95 percent, run 4x to 12x faster, and reduce inference cost by 50 percent to 80 percent while preserving performance. Independent and partner materials describe similar accuracy retention with materially lower compute use.
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• This also broadens Multiverse beyond its original quantum optimization niche. The company now spans evaluation, compression, hosted inference, and its own models, which makes it look less like a point solution and more like an efficient AI stack built around finding the cheapest model that still gets the job done.
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The next step is a tighter loop where evaluation automatically routes workloads into compressed deployment and then feeds production results back into the next round of testing. If Multiverse keeps owning that compare, compress, and deploy loop, it can win budgets before a frontier model vendor ever becomes entrenched.