Choose between buying software and building custom AI

A packaged AI product, a custom build and a private deployment each promise to meet the need. The buying group lacks a common way to compare them. Product showcases can cover different scenarios, and cost quotes include different responsibilities. Ownership, data exit, integration and ongoing evaluation can all be unclear until late in the process.

We build a fair comparison that tests every option against the same tasks and terms.

• Disqualifying requirements and representative tasks are agreed before any vendor scoring, drawn from must-have tasks, control requirements and integration constraints.
• Each candidate handles the same task panel and discloses its deployment, support and data boundaries.
• We compare task evidence, total operating assumptions and handoff rights. For each option we check source data, prompts, logs, backups, support access and export rights, and verify the actual private boundary.
• A missing critical requirement cannot be offset by a good average score. An unverified claim stays open as a diligence task. If candidates cannot be compared fairly, the panel is narrowed or a bounded proof is run first.
• Vendor submissions stay restricted. All candidates use authorized test data under the same permissions, and no confidential material goes into a trial without a defined boundary.

• A requirement-to-evidence comparison. Every option is scored against the same disqualifying requirements and representative tasks.
• An option and responsibility map. Who operates, supports and owns each part of every option, including data exit.
• A decision memo. A conditional recommendation, with remaining diligence, unsupported claims and exit conditions listed.

• Business owners approve must-have outcomes, and technology and security validate architecture and controls.
• Procurement and legal review operating, contract and exit terms.
• The sponsor selects the option within their actual authority.

Choose an existing product when it passes the critical tasks and can be operated under the required terms. Custom delivery fits material gaps in workflow, integration or control, and private deployment is a boundary choice to evaluate, not an automatic answer.

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