COST CONTROL

Stop reacting to cloud costs. Start getting ahead of them

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What You Get

Budget controls per team and cost bucket

One-click forecasting with ARIMA model

Rightsizing and optimization recommendations

Real-time anomaly detection and alerts

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The Challenge

Cloud costs move faster than most teams can track them

Most teams are managing cloud spend reactively. By the time the problem is visible, the budget has already moved.

Budgets are set once and never tracked in real time

Teams create budgets at the start of the quarter and revisit them at the end. There's no continuous view of utilization, which means overruns aren't caught until it's too late to act.

Cost overruns show up after the damage is done

When budget alerts are missing or delayed, teams find out about overruns through the invoice. Proactive monitoring is the exception, not the norm.

Forecasting is manual, slow, and often wrong

Building cost projections by hand is time-consuming and disconnected from actual usage patterns. Without automated forecasting, financial planning relies on guesswork.

Optimization opportunities are scattered across tools

Recommendations from AWS, GCP, and Azure live in separate consoles with no unified view or prioritization. Acting on them requires toggling between platforms and losing track of what's been done.

Anomalies compound silently before anyone is alerted

Cost spikes go undetected for days because monitoring is reactive. By the time teams are notified, the surge has already inflated the bill.

No shared view of cloud spend across teams

Finance, engineering, and leadership all look at different cuts of the same data. Without a single source of truth, reporting is inconsistent and decisions get made in silos.

What’s Inside

Built for teams who'd rather prevent overruns than explain them

Powered by Amnic's
cloud cost observability platform

Each feature tackles a different layer of cloud cost control, and they're built to work together.

Budgeting

Map and track budgets across every team

Distribute budgets across teams and departments, track utilization in near real time, and get ahead of overruns before they hit the invoice.

Build and track budgets by team, project, and department

Near real-time utilization monitoring

Predated budgets and cost bucket support

Explore Budgeting

Forecasting

Predictive views into anticipated cloud costs

Generate accurate cloud cost forecasts in one click, across any date range or provider, built on the ARIMA model and integrated directly into Cost Analyzer.

One-click forecasts across monthly, quarterly, or custom ranges

Total cloud or provider-specific breakdowns

ARIMA-powered for accurate trend prediction

Explore Forecasting

Recommendations

Tailored optimization across your infrastructure

Access Amnic-generated and cloud-native recommendations in one centralized dashboard spanning Kubernetes, AWS, Azure, and GCP, with no tool switching.

Rightsizing for compute, storage, and network

Kubernetes cluster and node optimization

Commitment coverage and savings plan recommendations

Explore Recommendations

Reporting

Automated reports, delivered on your schedule

Filter costs by date range, region, provider, tag, and more. Save custom views, share reports with stakeholders, and schedule automated delivery on any cadence.

Save, share, and schedule reports

Custom and pre-built category views

RBAC and cross-team collaboration

Explore Reporting

Anomalies

Detect cost spikes before they compound

Visualize anomalies across AWS, Azure, and GCP, define custom detection rules, and alert the right teams instantly via Slack, Teams, or email before overruns grow.

Custom and default anomaly detection rules

Kubernetes deviation monitoring

Instant alerts via Slack, MS Teams, and email

Explore Anomaly Detection

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Engineering Efficiency that
keeps up with the speed of code.

by Fortune 500s, Large, Mid-size and Startups

FROM ENGINEERING TEAMS

Achieved a remarkable 30% reduction in NAT Costs

"Amnic’s astute recommendation engine helped us reduce our cloud bill through optimization of network and cloudwatch costs. A key differentiator for Amnic remains its strong team which has channelized its significant experience in building a product uniquely suited to address pain points of fast growing companies."

Read the full case study

Mayank Bhola

Co-founder & CTO

FROM ENGINEERING TEAMS

Engineering Efficiency that keeps up with the speed of code.

by Fortune 500s, Large, Mid-size
and Startups

Reduced our cloud bill

"Amnic’s astute recommendation engine helped us reduce our cloud bill through optimization of network and cloudwatch costs. A key differentiator for Amnic remains its strong team which has channelized its significant experience in building a product uniquely suited to address pain points of fast growing companies."

Read the full case study

Mayank Bhola

Co-founder & CTO

E-books

Blogs

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In News

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How Amnic Helps

The same rigor you apply to cloud costs, now for AI

Amnic gives you full visibility into AI token usage across your organization so you can allocate costs accurately, spot inefficiencies early, and make smarter decisions about how and where AI is deployed.

Incomplete and inconsistent tagging

Resources across AWS, GCP, and Azure follow different naming conventions, and manual tagging leaves gaps that make cost categorization unreliable from the start.

No clear owner for cloud spend

When costs cannot be traced back to a specific team, product, or service, accountability breaks down, and budget conversations stall with no data to back them up.

Cloud spend feels disconnected from revenue

Finance and engineering are often working off completely different numbers. Without linking infrastructure costs to business outcomes, measuring ROI is nearly impossible.

Multi-cloud adds more fragmentation

Each cloud provider structures cost data differently. Trying to get a unified picture across multiple environments usually means stitching together spreadsheets that are outdated the moment they are built.

Insights arrive too late to act on

Monthly billing cycles and delayed reports mean cost anomalies go undetected until the damage is already done. By the time teams see the data, the spending has already happened.

No visibility into unit-level profitability

Knowing which customers or product lines are actually profitable requires more than billing data. Without cost allocation at the unit level, pricing and resource decisions are little more than guesswork.