Data readiness review
We sample the needed records for completeness, access, history, and label quality.
CAPABILITIES / STRATEGY AND DISCOVERY
AI readiness
An honest assessment of whether your data, systems, and controls can carry what you want to build.
What this covers
Systems and integration audit
Interfaces and ownership are checked against the read and write paths the use case requires.
Risk and compliance posture
Decision impact and data sensitivity determine the controls needed before a pilot can begin.
Discoverability by AI assistants
Public content and structured data are tested for how accurately assistants can find and describe the organization.
Gap remediation plan
Each blocking gap gets an owner, acceptance condition, and sequence tied to the target use case.
How it shows up in the work
BUSINESSESSell more to people and their agents.Half of B2B buyers now start in an AI instead of a search box. Being findable means being readable by machines, and being fast means an agent watching the orders your team can't read all of.ENTERPRISESOne platform for a growing agent workforce.The first agent is a project. The tenth is a platform problem. Shared retrieval, model routing, monitoring, and tuning are what make the second agent take weeks instead of months.NATIONSBuild the trusted national data and AI grid.Institutions hold data that would be worth more together, and they're right to be careful about sharing it. A grid makes sharing governed rather than informal.
WHERE IT FITS
Readiness is a discovery output and may lead to remediation before a proof of value starts.
