Case Studies/Cloud Sentinel
FinTechCloud InfrastructureCost Optimization

Cloud Sentinel

How we helped a Series C FinTech eliminate $1.8M in annual cloud waste through intelligent automation and predictive resource management.

$1.8M

Annual Savings

Reduction in cloud spend

35%

Cost Reduction

Overall infrastructure costs

12x

ROI

Return on engagement investment

12 weeks

Time to Value

From kickoff to production

Executive Summary

A 12-week engagement transforming cloud cost management for a high-growth FinTech.

A rapidly scaling Series C FinTech company approached us with a critical challenge: their AWS infrastructure costs had ballooned to over $450,000 per month, with no visibility into resource utilization or cost attribution. Engineering teams were provisioning resources without governance, leading to significant "zombie" infrastructure that served no production purpose but continued to accrue charges.

We deployed Cloud Sentinel, an AI-powered infrastructure optimization platform that combines real-time monitoring, predictive analytics, and automated remediation. Using custom Python agents and Meta's Prophet forecasting library, we built a system that not only identified waste but predicted future resource needs with 94% accuracy.

Within twelve weeks of deployment, the client achieved a 35% reduction in cloud spend—translating to $1.8M in annual savings. More importantly, the platform continues to optimize autonomously, ensuring sustainable cost efficiency as the company scales.

The Challenge

Four interconnected problems were driving unsustainable cloud costs and creating operational risk for the organization.

Resource Sprawl

Over 2,400 EC2 instances across 12 AWS accounts with no centralized visibility. Development teams provisioned resources without decommissioning processes.

Unpredictable Costs

Monthly cloud bills varied by 40%+ with no forecasting capability. Finance team struggled to allocate costs to business units accurately.

Manual Processes

Infrastructure team spent 20+ hours weekly on manual resource reviews. No automated enforcement of cost policies or lifecycle management.

Security Blind Spots

Zombie resources created attack surface vulnerabilities. Unpatched instances and forgotten S3 buckets posed compliance risks.

"We were hemorrhaging money on cloud resources we didn't even know existed. Every month, Finance would ask why our AWS bill was different, and we had no answers."

VP

VP of Engineering

Series C FinTech (Confidential)

Our Approach

A phased methodology combining deep technical analysis with sustainable automation that operates autonomously post-engagement.

1

Discovery & Audit

Weeks 1-2
  • Comprehensive AWS infrastructure audit across 12 accounts
  • Cost allocation analysis and tagging strategy review
  • Stakeholder interviews with Engineering, Finance, and DevOps
  • Identification of 847 untagged or orphaned resources
2

Architecture & Design

Weeks 3-4
  • Custom Prophet-based demand forecasting model development
  • Spot Instance interruption prediction algorithm design
  • Multi-account governance framework creation
  • Security and compliance requirements integration
3

Implementation

Weeks 5-8
  • Python agent deployment across all AWS accounts
  • Real-time monitoring dashboard implementation
  • Automated rightsizing recommendation engine
  • Slack/PagerDuty integration for anomaly alerts
4

Optimization & Handoff

Weeks 9-12
  • Model fine-tuning based on production data
  • Team training and knowledge transfer sessions
  • Runbook documentation and incident response procedures
  • Ongoing optimization playbook delivery

Technical Solution

Cloud Sentinel leverages a serverless, event-driven architecture designed for minimal operational overhead and maximum scalability.

Data Collection

CloudWatch, Cost Explorer, Trusted Advisor APIs

ML Processing

Prophet forecasting, anomaly detection, pattern recognition

Automated Actions

Resource rightsizing, Spot management, alerts

Technology Stack

Python

Core Language

AWS Lambda

Serverless Compute

Prophet

Time Series Forecasting

Terraform

Infrastructure as Code

CloudWatch

Monitoring

Cost Explorer API

Cost Analysis

EventBridge

Event Orchestration

DynamoDB

State Management

Results & Impact

Measurable outcomes delivered within the first 90 days of deployment.

Eliminated 847 zombie resources within the first month

Achieved 94% Spot Instance utilization with <2% interruption rate

Reduced average instance size by 23% through rightsizing

Implemented predictive scaling reducing over-provisioning by 31%

Established real-time cost anomaly detection with 15-minute alerting

Created automated compliance reports for SOC 2 and ISO 27001 audits

ROI Analysis

Engagement Investment

$150,000

12-week fixed-price engagement

First-Year Savings

$1,800,000

Annualized cloud cost reduction

Payback Period

31 Days

Time to recover investment

"The Lesos team didn't just optimize our cloud costs—they transformed how we think about infrastructure. Cloud Sentinel runs autonomously, and we haven't touched it in months. It just works, saving us money every day."

Chief Technology Officer

Series C FinTech, $200M+ Valuation

Key Learnings

Insights from this engagement that inform our approach to cloud optimization projects.

1

Visibility Before Action

The first two weeks of pure discovery and tagging paid dividends. You can't optimize what you can't see. Rushing to automation without proper visibility leads to suboptimal results.

2

Align Incentives Early

Engineering teams resist cost optimization when it threatens their velocity. Framing savings as "budget for new initiatives" rather than "cuts" changed the conversation entirely.

3

Automate with Guardrails

Autonomous optimization requires robust rollback capabilities. We implemented 15-minute observation windows before any automated action becomes permanent.

Is Your Cloud Spend Under Control?

Most organizations are overspending by 25-40% on cloud infrastructure. Let's discuss how we can help you identify and eliminate waste.