❏ Is the solution aligned to line-of-business outcomes (e.g., productivity, customer service, legal, healthcare, manufacturing, public sector)?

❏ Have you estimated Time to First Token (TTFT) and latency needs for your LLM workloads?

❏ Do you know the expected concurrency/user load (e.g., 32 concurrent users per 2-worker node for RAG)?

❏ Have you identified the primary AI/GenAI workloads (RAG, inferencing, fine-tuning, departmental LLMs, vector DB integration)?

❏ Are you evaluating CPU-based AI options (OPEA, Intel Xeon) versus GPU alternatives for cost/performance balance?

❏ Is your data pipeline ready (data prep, ETL, secure ingest into vector DB)?

❏ Do you require high availability, redundancy, or DR capabilities?

❏ Are you leveraging Ubuntu Linux / Kubernetes / Red Hat OpenShift AI stack support?

❏ Have you validated network performance (25–100GbE depending on workload)?

❏ Is storage provisioned with NetApp ONTAP + Trident CSI driver for Kubernetes persistence?

❏ Minimum 3 compute nodes (2 worker, 1 control plane) sized correctly?

❏ Are your containerized apps compatible with Kubernetes & Helm charts provided?

❏ Which vector database(s) (e.g., Milvus, pgvector) are planned for deployment?

❏ Do you need OPEA (Open Platform for Enterprise AI) pre-integration for retrieval-augmented generation (RAG)?

❏ Are you leveraging hybrid-cloud options (Cloud Volumes ONTAP, FSxN, Anthos, Azure Arc)?

❏ Do you need partner ISV integrations (ESRI, healthcare PACS, financial/legal ISVs)?

❏ Have you enabled role-based access control (RBAC) in Kubernetes?

❏ Is there a data protection & backup plan (SnapMirror, SnapCenter, ransomware protection)?

❏ Have you mapped data compliance needs (HIPAA, GDPR, FedRAMP, CJIS)?

❏ Do you require private AI deployment (air-gapped, on-premises, secure enclave)?

❏ Are admins trained/enabled on Kubernetes, Trident CSI, and OPEA stack deployment?

❏ Do you need support for multi-tenancy (departments, SLED agencies, business units)?

❏ Is there a plan for monitoring & observability (ONTAP System Manager, Cloud Insights, Prometheus/Grafana)?

❏ Who will own day-2 operations (customer IT, partner, managed service provider)?

❏ Is there a phased roadmap (departmental → enterprise-wide AI expansion)?

❏ Do you have a multi-year pro forma projection (TCO, ARR, margin uplift)?

❏ Are licensing uplift scenarios clear (vector DB, ISV software, AI ops tools)?

❏ Have you explored partner incentives (distributor margin, OEM/Intel co-funding)?

❏ Is the purchase aligned to budget cycles (CapEx vs OpEx, consumption models)?

❏ Do you have a services partner (Arrow, WWT, Presidio, etc.) for sizing & deployment?