A Practical Procurement Path for Indian Enterprise Teams

Frame the RFI around the workload and decision

Start with the business outcome and workload. Aitonomi AG can discuss dedicated GPU capacity: L40S 48GB for inference, vision, or rendering; H100 80GB each for training; and H200 141GB each for high-memory AI. These are planning examples, not availability or commitment.

• What use case, model, data scale, environment, and deployment phase are in scope?
• What GPU memory, single- or multi-GPU topology, capacity period, and start window are required?
• What evaluation evidence, decision date, internal owner, and procurement route govern the request?

Turn security and data review into specific questions

Document the controls and evidence your organization requires. Data location, transfer, residency, access, retention, encryption, identity, logging, incidents, and subcontracting require review against the proposed scope and terms; none is guaranteed here.

• Which data classes, jurisdictions, retention rules, and transfer restrictions must be addressed?
• What access model, audit evidence, security questionnaires, and contractual documentation are required?
• Which internal security, legal, privacy, and architecture approvals must occur before commitment?

Clarify commercial, support, and deployment boundaries

Request written scope for configuration, capacity period, managed-environment discussion, deployment-support responsibilities, and commercial terms. Confirm inclusions, exclusions, task ownership, change handling, and conditions before work begins.

• What eligibility checks, configuration assumptions, dependencies, and acceptance criteria apply?
• What support contacts, escalation path, response expectations, and customer responsibilities are proposed?
• What pricing basis, term, renewal, change process, termination provisions, and governing documents apply?