One decision. Three owners. One evidence package.
Enterprise AI should survive business, finance, and technical review at the same time. Start with the decision, the measured outcome, and the person who remains accountable. Then inspect the economics, operating boundary, and record the system creates.
Legal approval
Contract to production
Q1 net savings validated by customer finance
Locations nationwide
Agree on five things before comparing platforms.
Agents, workflows, integrations, governance, and deployment options now appear across many enterprise AI platforms. The useful buying test begins below the feature layer.
- 01Decision
What repeated high-stakes choice should improve?
- 02Outcome
Which later business result determines whether it worked?
- 03Evidence
Which records were available before the decision?
- 04Authority
Who can question, edit, approve, delay, or decline?
- 05Boundary
Where may data, models, agents, and traces operate?
Each owner reviews the same decision from a different risk.
The guides are designed to be used together. Passing one review does not substitute for the other two.
The CFO guide to decision economics
Is the value calculation defined before the model is evaluated?
The CHRO guide to better talent decisions
Does the decision improve a talent outcome the business already trusts?
The CISO guide to a governed decision engine
Where do data, models, agents, traces, and telemetry operate?
Leave the buying meeting with artifacts, not adjectives.
- Decision BlueprintOutcome, population, evidence, policy, owner, actions, and abstention rules.
- Decision Replay resultHistorical evidence, counterexamples, limitations, and the agreed value calculation.
- Deployment mapData paths, model access, agents, workflows, traces, telemetry, and exit terms.
- Decision Trace sampleRecommendation, human input, approved action, and the measured result that followed.