Scope an evaluation around an operating problem.
Describe the outcome that is falling short, the workflow involved and the decision the team needs to make. Include the current metric definition and the source records behind it. If the measure is inconsistent, resolving its definition may be the first deliverable.
Agree which teams, systems, time periods and constraints are in scope. Also record what the evaluation cannot yet answer. The work may lead to a supported diagnosis, a compared proposal, a prototype or a request for evidence needed before a meaningful test can proceed.
Start with authorized exports.
An initial technical evaluation can use exported files such as CSV, SQLite datasets and process documents. This allows the team to define a bounded data snapshot for review without assuming a live connector is already available. Integration requirements are assessed for the specific deployment.
Agree necessary fields, format, time coverage and links between records. Specify how identifying information will be removed or transformed before use, and check the prepared data. Missing data, inconsistent statuses and incomplete histories should be documented rather than silently filled with assumptions.
Set the processing and access boundaries.
Polaris supports deployment in a customer-controlled cloud. The project must still define where source data, model calls and evaluation artifacts are processed; which providers are involved; who may access each part; and how retention and deletion are handled.
Confirm these choices with the customer’s technical and data owners before transferring materials or granting access. Customer-cloud deployment alone does not describe every model or network boundary. Any requirement concerning shared-model training or data reuse must be reflected in the agreed configuration and terms.
Identify the people who can resolve questions.
A business owner defines the operating question and outcome. A data owner confirms provenance, definitions and authorized use. A technical owner reviews deployment constraints and any executable changes. Polaris investigates the supplied evidence, develops candidates and records their validation scope.
During evaluation, missing information may require a targeted request to the relevant owner. The request should state the fields, period and purpose. If the information cannot be supplied, record how that gap affects the proposed decision.
| Responsibility | What to agree |
|---|---|
| Business owner | Goal, baseline, quality requirements and pilot decision |
| Data owner | Source definitions, export scope and preparation |
| Technical owner | Access, deployment constraints and change review |
| Polaris team | Investigation, candidate evaluation and evidence-based delivery |
Make the next step explicit.
The evaluation should assemble the baseline, findings and their evidence, alternatives considered, completed checks, remaining assumptions and proposed next actions. Reproducible calculations or prototypes belong with the relevant findings so reviewers can inspect how conclusions were reached.
A production pilot is a separate step. Agree its owner, cost, duration, acceptance criteria, observation window and rollback conditions before implementation. Deployment timing and commercial terms depend on the scoped work and data readiness; they are settled with the team rather than inferred from an offline test.
Questions before an evaluation
Can we evaluate Polaris before connecting live systems?
Yes. A scoped technical evaluation can begin with authorized exported records and documents. The available evidence determines which questions can be investigated.
What should we include in the first enquiry?
Describe the problem, the teams involved, the metric you track and the types of records available. Avoid sending sensitive records before the data scope and handling arrangements are agreed.