Enterprise AI platform evaluation guide
Compare the assembled platform across models, data, identity, evaluation, operations, cost, and exit.
An architecture-and-operations review for technology executives deciding how AI should enter the enterprise stack, which controls must follow it, and where vendor demonstrations leave material questions unanswered.
Guides for defining the job, evidence, control, pilot, implementation, and review before treating an AI capability as an operating result.
Compare the assembled platform across models, data, identity, evaluation, operations, cost, and exit.
Define tools, authority, state, approvals, telemetry, recovery, and accountability before an agent reaches production.
Test permission-aware retrieval, freshness, authority, citations, conflicts, and correction handling.
Measure infrastructure, model, data, integration, evaluation, review, security, support, and change costs per useful workload.