7-Day Cloud & AI Cost Diagnostic
A focused diagnostic for organizations that need a clearer view of cloud, AI, and infrastructure spending before making high-impact technical or financial decisions.
The standard diagnostic is delivered within seven working days after the agreed data, access and stakeholder information are available.
Spending is rising before the cause is clear
Cost issues are often not one problem; they are a mix of architecture, visibility, governance, utilisation, and commercial decisions.
Cost ownership is unclear
Cloud and software spend is growing faster than accountability, making it difficult to explain where money is going and who owns it.
AI economics are not visible
Training, inferencing, GPU, storage, and token costs are often tracked separately from business value and performance outcomes.
Auto-scaling masks inefficiency
Resources scale quickly but remain oversized, duplicated, idle, or inefficiently configured beyond actual demand.
Savings plans carry risk
Commitments or redesigns may reduce cost but create new operational risk if they are not mapped to real workload behaviour.
A practical and evidence-led review
The diagnostic is designed to help leadership and engineering teams understand where spend is going, what is efficient, and what should change.
- Technology-spend baseline and cost ownership review
- Cloud, storage, data transfer, and licence cost analysis
- Resource utilisation and idle-capacity assessment
- Rightsizing and scheduling opportunities
- Compute commitment and reserved-capacity scenarios
- AI workload cost review across model, GPU, token, and inference patterns
- Reliability and service-risk assessment
- Optimisation roadmap with implementation priority and effort
- Executive summary and decision support pack
Pricing
Engagements start from US$500
Typical engagements begin at US$500 and vary by environment complexity, analysis depth, access requirements, and time needed for meaningful review.
The diagnostic is generally most valuable for organizations with material recurring cloud or AI expenditure, complex allocation requirements, or an upcoming infrastructure commitment.
How the 7-day assessment works
Fit call
We align on the scope, environment, indicative cost profile, questions, and decision timeline.
Data and access review
We confirm what data is available and what access is required for a safe and useful assessment.
Baseline and drift review
We establish current spend, cost drivers, service patterns, and deviations across environments and workloads.
Analysis and recommendations
We assess utilization, performance, capacity, commitments, architecture, and possible commercial and technical improvements.
Prioritised roadmap
We rank recommendations by expected value, implementation effort, risk, and confidence level.
Executive readout
You receive a clear briefing for leaders, engineering teams, and operational stakeholders.
What we normally need
Cloud billing and cost reports
Usage and utilisation history
Architecture diagrams or current environment descriptions
Known bottlenecks, service levels, and constraints
Cost ownership and approval structure
AI workload or model deployment information where relevant
Security access and data-handling requirements
An assessment for teams that need clarity, not guesswork
- You have enough meaningful cloud or AI spend to justify a dedicated review.
- You want a fact-based view before committing to major cost or architecture changes.
- You need a realistic, risk-aware recommendation rather than a generic savings checklist.
- Your team wants specialist support without building a full internal FinOps capability from scratch.
Not suitable when
- technology spend is too small to justify specialist review
- the organization cannot provide billing or usage data
- there is no interest in investigating root causes or trade-offs
- the objective is a guaranteed savings claim without evidence
Responsible access and governance
We align access, confidentiality, and implementation risk before making recommendations.
Least-privilege access
Access is limited to the data and systems needed for the assessment.
Clear assumptions
Findings are presented with their confidence level and the assumptions used.
Risk-aware alternatives
Recommendations are weighed against uptime, resilience, and business continuity.
Implementation support
If approved, implementation and validation can be aligned with technical delivery capacity.
Common questions
What is included in a 7-Day Diagnostic?
A focused assessment of your technology spend, the main cost drivers, waste and inefficiency patterns, and a prioritised roadmap for improvement.
Does this include implementation work?
The diagnostic focuses on assessment and recommendations. If approved, Enikai Systems can support implementation, validation, or managed optimisation support.
Is this only for cloud costs?
No. The same discipline applies to broader technology spend, AI workloads, and infrastructure economics where operational stability and cost accountability matter.
How do you work with incomplete data?
The assessment is designed to work with available reporting, operational context, and access constraints. We show the confidence level and assumptions used so decisions remain evidence-based.
Need a clearer view of your technology spend?
A short fit call can help determine whether a diagnostic is the right next step for your environment.
A direct fit call confirms whether the diagnostic is the right next step for the operating environment.