Many AI projects fail to deliver expected outcomes due to legacy system incompatibilities, unrealistic expectations, or a lack of rigorous financial tracking. Data projects fail due to improper guardrails, overspend, underuse, etc. Internal teams often face political pressure to continue failing projects. This engagement offers a neutral, data-driven perspective to determine the viability of your AI strategy.