Private AI
Some work should not go through a shared public AI service. Private AI keeps models and data in environments you control — your building, a Growth Mode-hosted environment, or your own cloud account.
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The right answer depends on data sensitivity, workload size, latency, budget and who will operate it.
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A private model still needs patching, access control, monitoring, capacity planning, backups and someone to call. That operational layer is what Growth Mode manages.
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We evaluate open-weight models you can run yourself alongside private endpoints from major providers, and match them to tasks rather than benchmarks.
Performance and cost depend on models, hardware and usage. We size environments from your actual workloads and state assumptions in writing.
For many focused tasks, well-chosen private models perform well. For others, a private enterprise endpoint from a major provider may be a better fit. We test against your real work.
It depends on usage patterns. Steady heavy workloads may favor owned hardware; variable workloads often favor cloud. We compare the options for your case.
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