Built for AI in production.
Cube Optima pays off hardest when AI is wired into the work itself: the data you process and the traffic your customers generate. At production volume, a cluster you own costs a fraction of metered inference, and nothing leaves your infrastructure.
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Document & data pipelines
Extraction, classification, enrichment and summarization running across millions of records. Per-token pricing scales linearly with your data volume; a cluster you own does not.
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AI inside your product
Chat, support, search and recommendations embedded in a customer-facing app. Every session is inference, so a good traffic month turns straight into a bad invoice.
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Agents and coding fleets
Long-running agents that plan, call tools, retry and review. A single agent task burns orders of magnitude more tokens than a chat message, and your team runs them all day.
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RAG over proprietary corpora
Long-context retrieval across contracts, tickets, source code and internal records. Prefill-heavy by nature, and built on exactly the material you cannot send to a third party.
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Batch jobs and backfills
Reprocessing history every time a prompt, schema or model changes. On owned capacity a full backfill runs overnight at no marginal cost instead of triggering a budget review.
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Regulated and air-gapped work
Data residency requirements, regulated records, defense and finance. When inference has to happen inside your perimeter, self-hosting is the only configuration that qualifies.