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Buyer’s guide to private AI inference
If you’re investigating a private inference platform, what should you look for? Our buyer’s guide gives you four key questions to use with your vendors when evaluating a platform, plus five detailed worksheets to help engineering, security, and finance agree on a shortlist.
What you’ll learn
Private AI is a buying decision your whole team has to live with. Use this guide to turn competing priorities into requirements you can test, and compare approaches before committing to a platform. We’ve included the working tools, so you don’t have to start with a blank spreadsheet.
- Test platforms against four requirements: execution control, model routing, spend management, and day-2 operations.
- Align the buying committee and classify workloads with worksheets that make each team’s requirements explicit.
- Compare DIY, hosted services, AI gateways, and packaged private platforms, then build a shortlist with a weighted vendor scorecard.
- See an illustrative eight-GPU cost model, including operations and frontier fallback, to challenge the assumptions in your own business case.
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Get your free guide and all five worksheets
Fill in the form to get the complete guide, including the evaluation tools for your next vendor discussion.
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