HyperLake — An AI analyst on governed company data: start with one decision
FREE PLANNING CHECKLIST

Analyst combines the lakehouse, private models and agent sandboxes. Scope one business question, its permitted evidence and the checks a human reviewer will apply.

Prepare these inputs
[ ] A business question and trusted reference answer
[ ] Approved datasets and metric definitions
[ ] Roles, permissions and review criteria

Your first workflow
[ ] Choose one decision and define what a useful answer must contain.
[ ] Configure data permissions and semantic definitions.
[ ] Compare outputs with trusted analysis before expanding the audience.

Acceptance checks
[ ] Check calculations and evidence links.
[ ] Test role-based differences in visibility.
[ ] Review missing data and uncertain conclusions explicitly.

Decision criteria
[ ] Are the business definitions and data owners agreed?
[ ] Can each intended role access the required evidence?
[ ] Which answers require human review before use?

Cost and scope
Compare the cloud bill, platform charges, operating effort and migration work for the same workload. Cloud capacity is not free. Charges and scope need agreement before paid deployment.

Before switching
AWS and Google Cloud are available today; other deployment environments are roadmap. Preserve the existing workload and access path until compatibility, recovery and cutover checks pass.

Sources
https://hyperlake.cloud/stacks
https://hyperlake.cloud/faq
https://hyperlake.cloud/get-started

Next step
No free cloud capacity is promised. Deployment scope and charges are agreed separately; AWS and Google Cloud are available today.
https://hyperlake.cloud/solutions/governed-ai-analyst

This is a planning template, not a completed assessment or a quote. No personal data is required to download it.