FinOps-led optimization for AWS, Azure, GCP, and Kubernetes. From the team that built Fintropy — our 470-rule FinOps platform.
Built in India · Serving enterprises across India and English-speaking markets
Every FinOps assessment we run surfaces the same five patterns. Specific, named, and recoverable.
EC2/VMs/AKS nodes running at <10% utilization, GPU instances left on overnight, oversized databases.
Costs landing in "unassigned" — finance can't show back, engineering can't optimize.
Over-commit to RIs/SPs, under-use coverage, missed Azure Hybrid Benefit and GCP CUDs.
Cost spikes detected days late. No runbook for who responds when alarms fire.
No policy on tagging, budgets, or provisioning. Optimization wins decay within months.
Looking for broader IT cost coverage including SaaS licensing and on-premise modernization? See our IT cost optimization services.
We follow the FinOps Foundation framework. Each phase has concrete deliverables, not slideware.
Cost visibility you can act on.
Reduce spend where it's safe to reduce.
Make the savings stick.
The capabilities every engagement draws from, mixed to fit your environment.
Compute, databases, and storage tuned to actual workload patterns — not what someone guessed at provisioning time.
Coverage analysis and commitment recommendations for AWS Savings Plans, Azure Reservations, and GCP Committed Use Discounts.
Real-time spike detection with runbooks that route the alert to whoever can actually fix it.
Tag taxonomy, enforcement policies, gap remediation, and reporting that finance can stand behind.
Unattached volumes, orphaned snapshots, dormant load balancers, dev environments left running over weekends.
FinOps Foundation FOCUS 1.2 schema applied across AWS, Azure, and GCP so cross-cloud reporting is finally honest.
Pod-, namespace-, and label-level attribution across EKS, AKS, GKE, and OpenShift. Idle workload detection.
Forward-looking forecasts tied to engineering plans, not last quarter's straight-line extrapolation.
Multi-cloud, multi-runtime. The levers that matter on each platform.
Fintropy is the FinOps platform our engineering team built and uses on every engagement. 470 scan rules across AWS, Azure, GCP, Kubernetes, and VMware. FOCUS 1.2 billing. Automated SLA-breach credit claims. Real-time anomaly detection.
Three weeks from kickoff to a prioritized roadmap. Then we execute, you ship.
We connect to your AWS, Azure, GCP, and Kubernetes accounts (read-only) and run them through Fintropy. You receive a findings report.
We walk you through the report — ranked by dollar savings and implementation effort, with the assumptions and trade-offs behind each recommendation.
A prioritized 90-day optimization roadmap with named owners — yours, ours, or shared — and a baseline you can measure against.
We implement, you ship. Monthly FinOps reviews keep the savings compounding and surface the next round of opportunities.
FinOps assessments are fixed-fee and scoped to your cloud footprint. Ongoing engagements are typically retainer-based, sized to the number of accounts and optimization scope. Most engagements pay for themselves within the first quarter through identified savings.
Three weeks from kickoff. Week 1 is data collection and Fintropy scan. Week 2 is findings review. Week 3 is the prioritized 90-day roadmap. Larger or more federated environments can extend by a week or two.
Yes — all three, plus Kubernetes (EKS, AKS, GKE, OpenShift) and VMware (vSphere, VCF). Our Fintropy platform normalizes billing across them using the FinOps Foundation FOCUS 1.2 schema.
Cloud cost optimization is the act of reducing spend — rightsizing, commitments, cleanup. FinOps is the operating practice that makes those reductions stick: cross-functional ownership, governance, and a culture where engineers see cost as a first-class quality attribute. We do both; this page is about the services side.
No, and we'd encourage skepticism toward anyone who does. Realistic savings depend on your current maturity, commitment posture, and how much your engineering team can absorb. What we do guarantee: a transparent assessment, a prioritized roadmap, and a baseline you can measure us against.
No. Fintropy is what our team uses to deliver — you can engage us for services without adopting the platform. That said, most clients end up using it because it's the same tool we'd be using to run their engagement anyway.
Native tools show you what happened. They don't normalize across clouds, they don't enforce tagging policy, and they don't walk you through which 90 days of changes will move your bill the most. That's what the service — and Fintropy — does on top of them.
There's a fair-fee floor where a custom engagement starts to make sense — typically around $50K/month in committed cloud spend. Below that, Fintropy self-serve can carry most of the load and we'd point you there first.
Yes. Engagements with India-headquartered clients are priced and invoiced in INR. Pricing reflects local market norms while the deliverables — Fintropy scan, prioritized roadmap, governance setup — are identical to our global engagements.
Fintropy reads billing exports and read-only API data from your cloud accounts. We support deploying the scan tooling within your India region, and all sensitive findings are stored in line with DPDP, RBI, and SEBI guidance where applicable. We can sign a data processing addendum as part of onboarding.
Yes. Multi-cloud cost optimization is core to our practice — most of our engagements span AWS, Azure, and GCP simultaneously, with Kubernetes and VMware as recurring sub-estates. Consultation starts with a unified, FOCUS-normalized view of spend across all clouds in week one, then prioritizes the cross-cloud savings levers (commitment reshuffling, workload placement, egress reduction) in week two. A multi-cloud consultation is a fixed-fee engagement; talk to us if you run two or more major clouds.
Most cloud cost optimization companies are either generalist IT consultants who treat FinOps as one of many service lines, or pure tool resellers who hand you a dashboard and disappear. Nuvika is different: FinOps is the practice, not a side offering. We built and operate our own scan engine (Fintropy, with 470 rules across AWS, Azure, GCP, Kubernetes, and VMware), we deliver fixed-fee assessments with a 90-day roadmap, and we offer outcome-aligned pricing including savings-share. We are an India-headquartered firm with INR-priced engagements for Indian clients, which most global cloud cost optimization companies do not provide.
The standard industry range is 20–40% reduction on cloud spend. The spread reflects starting conditions: a cloud estate that has grown fast without dedicated FinOps attention sees the higher end; an already-mature environment sees less. On $1M/year that translates to $200,000–$400,000 back annually. Nuvika assessments include a transparent savings estimate in week one, before any ongoing engagement begins.
Yes. GCP cost optimization is a core part of our multi-cloud practice. Fintropy covers GCP-specific waste patterns — Compute Engine right-sizing, BigQuery cost management, Cloud SQL optimization, and committed use discount strategy. GCP engagements follow the same fixed-fee three-week assessment model as AWS and Azure.
Yes. Azure is the dominant cloud for large Indian enterprises and our Azure practice reflects that depth. Fintropy runs 149 Azure-specific optimization rules covering VM right-sizing, Azure Firewall, DDoS Protection, Synapse dedicated SQL pools, Bastion utilization, and Reserved Instance strategy. Engagements are INR-priced and include DPDP, RBI, and SEBI compliance overlays where relevant.
For Indian enterprises, India-headquartered specialists offer INR-priced engagements that are significantly more cost-effective than global firms billing in dollars. A fixed-fee three-week assessment covers discovery, a Fintropy scan, and a prioritized 90-day savings roadmap — at a fraction of what a global SI would charge for the same deliverable. Payback is typically within the first quarter of implementation.
At $1M+/month spend the native tools (AWS Cost Explorer, Azure Cost Management, GCP Cost Tools) stop being sufficient — they don't normalize across clouds, don't enforce tagging policy, and don't model commitment portfolios. Specialist platforms become essential: Apptio Cloudability, CloudHealth, Spot.io, Vantage, and Nuvika's own Fintropy (470 scan rules with FOCUS 1.2 normalization across AWS, Azure, GCP, Kubernetes, VMware). The decision is usually less about which tool and more about whether to pair it with a FinOps team — at $1M/month the team cost is justified by the savings.
Enterprise FinOps platforms typically price as a percentage of cloud spend (1–3%) or via tiered subscriptions. At $1M/year cloud spend, expect $10K–$30K/year for a platform; at $10M/year spend, $50K–$200K/year is common. Nuvika's Fintropy has transparent pricing tiers published at /pricing.html. Consulting engagements are separate and priced fixed-fee — see /pricing-services.html for ranges.
For rightsizing alone, AWS Compute Optimizer (free, native) is among the strongest engines for EC2; Azure Advisor and GCP Recommender are improving but lag in commitment modeling depth. For multi-cloud commitment portfolio analysis (RIs vs Savings Plans vs CUDs across clouds), independent platforms like Fintropy, Spot.io, and Cloudability outperform native tools because they reason across cloud boundaries. The best engine depends on whether you need accuracy (native) or cross-cloud flexibility (independent).
Yes. Fintropy publishes its pricing at /pricing.html (Core, Growth, Enterprise tiers) and typical onboarding is 1–7 days depending on cloud-account access setup. Vantage and Cloudability also publish pricing and offer fast self-serve onboarding. Avoid vendors who require a sales call before disclosing pricing — that pattern usually means setup is not under 2 weeks either.
India-headquartered clients are invoiced in INR. Ranges are indicative — scope locked at SOW after a 30-minute discovery call.
See all service pricing →India-headquartered with INR-priced engagements and remote-first delivery. We work with enterprises and digital-native teams across Mumbai, Pune, Bangalore, Delhi NCR, Hyderabad, and Chennai — and run on-site workshops in each metro when a kick-off needs the room.
For BFSI, capital markets, and large enterprises — RBI-aware data residency, NPCI workload patterns, and TRAI-compliant telco infrastructure.
For IT services GCCs, auto-tech, and SaaS scale-ups — VMware estates, Kubernetes platforms, and multi-tenant SaaS unit economics.
For product companies and venture-backed startups — Series B+ burn discipline, GPU/AI infra economics, and AWS commit strategy.
For Delhi, Gurgaon, and Noida — enterprise Azure estates, telecom workloads, and government-of-India compliance overlays.
For Hyderabad's pharma-tech, life sciences, and global capability centres — Azure-heavy estates and AI infra cost discipline.
Remote-first delivery across all major Indian metros. Talk to us about your city.
FinOps is one of many service lines for generalists. For us, it is the practice.
| Dimension | Generalist IT consultant | Nuvika |
|---|---|---|
| Practice focus | One of many service lines | FinOps & IT cost is the practice |
| Tooling | Vendor-resold dashboards | Fintropy (470 rules, listing on Azure Marketplace) |
| Cloud depth | Surface multi-cloud | AWS · Azure · GCP · K8s · VMware · FOCUS-billing native |
| SaaS & shadow IT | Often skipped | Discovery + license rationalization included |
| On-prem & legacy | Hardware refresh playbook | Modernization-led: keep · retire · replatform · rehost |
| Pricing model | T&M heavy | Outcome-aligned; savings-share available |
| India presence | Offshore delivery only | India HQ + India-priced engagements |
Looking for something different? Here's where to go next.
Building a FinOps practice rather than one-off optimization? See the long-term program offering.
The 470-rule platform we built — multi-cloud waste detection, FOCUS billing, SLA-breach claims.
FinOps-aware migrations across Azure, AWS, GCP, and VMware workloads.
Cloud, SaaS licensing, shadow IT, and on-premise modernization — for Indian enterprises and India delivery centers.
Deeper analysis on AI infrastructure costs and the balance-sheet case for FinOps.
Excellence in ML rarely correlates with efficient infrastructure. Seven concrete optimization strategies that don't sacrifice model accuracy.
Cloud costs are now a balance-sheet story. How to build a cost strategy that survives board scrutiny.
Ready to optimize your cloud costs? Schedule a free consultation with our team.
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