| Rev | Description | Drafted by | Checked by | Approved by |
|---|---|---|---|---|
| Waiting for the first survey pass… | ||||
Simulated estate with illustrative data. Not client results.
We combine AI agents, intelligent automation, and advanced cloud engineering to eliminate infrastructure waste, optimize workloads, and design cloud environments that scale efficiently. From cost intelligence to cross-cloud modernization, we turn infrastructure complexity into measurable business value.
Works across AWS / Microsoft Azure / Google Cloud / alternative providers
A-100 Existing conditions
Every new team, service, and region adds resources sized for peak, monitoring that lives in its own tool, and spend that is hard to attribute. Provisioned capacity drifts away from real demand, architecture accumulates layers nobody revisits, and the monthly bill gets harder to predict and harder to explain.
Networqing Cloud is the engineering partner that systematically discovers, quantifies, and addresses these inefficiencies.
Instances, volumes, and clusters sized for a peak that rarely arrives, then left running.
Accounts, services, and network paths added faster than anyone rationalizes them.
Billing, telemetry, and configuration data spread across tools that are never correlated.
Usage-based pricing, data transfer, and commitments drifting out of line with demand.
Engineering hours lost to manual reviews, ticket-driven cleanups, and one-off audits.
How we address it
A-200 Scope of work
From infrastructure discovery and cost intelligence to configuration optimization, cross-provider migration, and predictive capacity planning. Each discipline is drawn below as a detail of the same set.
Detail 1 · NTS
AI-assisted analysis across your existing environments finds underutilized resources, inefficient configurations, unnecessary spend, and architectural bottlenecks. We correlate billing data, infrastructure telemetry, workload utilization, and configuration metadata, so every recommendation carries a measurable technical and financial impact.
IncludesBilling correlation / utilization telemetry / config metadata / impact scoring
Detail 2 · NTS
Data-driven optimization of compute, storage, networking, databases, container workloads, and resource allocation. We find rightsizing, autoscaling, workload scheduling, storage lifecycle, and simplification opportunities, then implement them safely through policy-driven automation and engineering validation.
IncludesRightsizing / autoscaling / workload scheduling / storage lifecycle / automated remediation
Detail 3 · NTS
We evaluate workloads across AWS, Microsoft Azure, Google Cloud, and alternative providers to find more cost-effective deployment strategies. Roadmaps weigh total cost of ownership, performance, licensing, data transfer, availability, security, and operational complexity, and we carry the move through infrastructure-as-code and post-migration optimization.
IncludesTCO modeling / migration roadmaps / infrastructure-as-code / service modernization
Detail 4 · NTS
Forecasting models built on historical utilization, workload patterns, and your business growth assumptions. Capacity plans, spending forecasts, architectural scenarios, and scaling strategies prepare you for growth without excess provisioning or unexpected cloud spend.
IncludesDemand forecasting / spend forecasts / scenario modeling / scaling strategy
Detail 5 · NTS
An ongoing program that analyzes infrastructure changes, monitors spend, detects inefficiencies, and surfaces new opportunities. Automated discovery, anomaly detection, policy-based recommendations, approval workflows, and recurring performance reporting make optimization an engineering discipline rather than a one-time audit.
IncludesAnomaly detection / approval workflows / policy recommendations / recurring reporting
Detail 6 · Wall section · NTS
Security posture is evaluated alongside cost and performance. Every optimization accounts for identity and access management, network exposure, encryption, backup coverage, data residency, availability, and compliance, so expenditure comes down without new vulnerabilities, reliability issues, or operational risk.
IncludesIAM / network exposure / encryption / backup coverage / data residency / compliance
A-300 Approval authority
Networqing Cloud is an AI-native consulting practice. Intelligent agents and automated engineering workflows accelerate infrastructure assessment, correlate complex datasets, generate optimization strategies, model architectural alternatives, and assist with implementation.
Like any drawing set, nothing is issued without sign-off. Deterministic analysis checks every revision, and cloud engineers approve high-impact changes before anything is implemented.
| When | By | Entry |
|---|---|---|
| t+4s | Agent | Correlated 30 days of utilization with billing line items. CPU p95 14%, memory p95 33%. Candidate: one instance class smaller. |
| t+6s | Model | Monthly cost recomputed from the current rate card. Reserved capacity checked: no commitment conflict. Post-change headroom stays above the 30% policy floor. |
| t+7s | Policy | Encryption at rest, backup retention, and multi-AZ failover unchanged. Classified high impact: stateful and customer-facing. |
| day 2 | Engineer | Reviewed by a cloud engineer. Approved for the Tuesday maintenance window with a tested failover plan. |
| day 5 | Execute | Terraform plan opened as a pull request, reviewed, and applied in the window. Rollback path: revert the commit. |
| day 19 | Verify | Fourteen days of post-change utilization inside the target band. Cost change confirmed against billing data. Revision closed. |
General notes
A-400 Sequence of work
Each stage produces something you can inspect. The last one feeds the first, so optimization keeps pace with how your infrastructure changes.
Integrate with existing infrastructure and collect relevant billing, configuration, and utilization data.
Apply AI-assisted intelligence and quantitative analysis to identify inefficiencies and risk.
Develop prioritized optimization strategies, architectural recommendations, and migration plans.
Implement approved changes using automation, infrastructure-as-code, and engineering oversight.
Continuously monitor outcomes, validate savings, and identify further improvements.
A-500 Performance specification
The method for each outcome is written down before work starts, and every result is measured against your own pre-engagement baseline. Spend less, operate smarter, and scale with confidence, with the evidence to show for it.
Section 01 81 00Performance requirements · Part 1 · Outcomes
Validated run-rate change against the pre-change baseline, net of commitments.
Δ run-rate vs. baselineConsumed versus provisioned capacity across compute, storage, and databases.
consumed ÷ provisionedVariance between forecast and actual spend, by service and by team.
|forecast − actual| ÷ actualElapsed time from data access to a prioritized, quantified findings report.
t(access → findings)Share of changes shipped as reviewed code with a tested rollback path.
changes via IaC + rollbackProvisioned headroom tracked against forecast demand over time.
headroom vs. forecastCoverage of telemetry, cost allocation, and security posture checks across environments.
coverage by environmentA-600 Issue options
We recommend starting with an assessment. What it finds decides whether a project, a continuous program, or both come next.
Fixed scope Start here
A fixed-scope review of infrastructure, spending, architecture, and optimization opportunities.
Project-based
Project-based implementation, architecture redesign, and cloud migration.
Recurring
Recurring AI-assisted monitoring, optimization analysis, reporting, and engineering support.
A-700 Request for assessment
Discover where your infrastructure can operate more efficiently, what it should cost, and how to build for what comes next.
The assessment covers