Your decision
Can the proposed solution fit the technology estate, data model, and operating responsibilities?
GENELLIPSE FOR ENTERPRISE
Assess architecture, integration, data readiness, and operational fit.
THE DECISION BEHIND THE TECHNOLOGY
A technical evaluation must get beyond a feature demonstration. Understand the integration boundary, workload, control surface, and operating burden. A solution that performs well in isolation can still fail when sources change, queues back up, or access rights differ across teams.
Select a stage to inspect its owner, evidence, and stopping condition.
CONTROLLED PROGRESSION
Locate systems of record, interfaces, data classifications, and constraints. Identify which capabilities are retained, wrapped, or replaced.
Illustrative evaluation: a legacy batch supplies data to an AI-enabled reporting workflow. Test a late file, a schema change, and a repeated job before declaring the interface complete. The handover must explain who notices each failure and how the service recovers without duplicating output.
Use these prompts with your team. Checked items are a local working aid, not a readiness certification; they reset when you leave this guide.
0 / 4prompts reviewed
Use this guide to align the right stakeholders before a demonstration or MVP.
Can the proposed solution fit the technology estate, data model, and operating responsibilities?
Use GeneData for the data foundation, Cortex AI for governed agent workflows, and the relevant domain product for business context. Assess existing interfaces and approved environments.
Identity, data lineage, permitted model services, network boundaries, workload volumes, observability, recovery, and change management.
A solution blueprint, interface contracts, test results, deployment assumptions, responsibility matrix, and operational runbook.
Connect one representative source to one reviewed output, with a measurable quality check and a documented failure path.
Each question should produce an artifact that engineering and operations can review. Product names alone do not answer architecture questions.
Identify authoritative records, caches, indexes, intermediate outputs, and audit events. Explain retention, consistency, and which copy wins when values disagree.
Trace identity from user to agent to tool to backend. Separate discovery of a tool from authorization to use it. Confirm credential scope and the handling of privileged or unattended work.
List APIs, models, prompts, schemas, dependencies, and vendor services that can change. Define compatibility tests, version pinning where appropriate, and rollback expectations.
Require correlation across inputs, decisions, external calls, and final status. Measure stuck work and partial success rather than relying solely on infrastructure availability.
A weighted average can conceal a critical defect. Score fit and effort, but keep mandatory security, data integrity, and recoverability gates separate.
Document supported interfaces and configurations, required customization, constraints, and any gaps. Confirm commitments in the proposed scope.
Include customer engineering, data remediation, testing, identity integration, procurement, and operating readiness in the estimate.
Attach a reproducible test or reviewed design to each material conclusion. Unverified capabilities remain open questions rather than receiving a favorable score.