Finlex cuts cloud costs 50% and ships production AI with DoiT
- Over 65%
- reduction in cloud infrastructure costs from 2024 - present
- 40%
- cost savings achieved through improved visibility and efficient AI architecture
The Challenge
Island lacked visibility into true cost per customer and cost per feature. Billing data showed what was spent but not what was driving costs at the application layer. The company runs a sophisticated AWS environment with heavy use of shared resources like EKS, RDS, DynamoDB, and AZ-to-AZ data transfer. Allocating these shared costs in a multi-tenant architecture was effectively impossible with native cloud tools and third-party platforms. Tagging wasn't a solution either, requiring heavy setup, constant maintenance, and unable to reliably capture customer-level consumption.
The Solution
Attribute™'s FinOps without Tagging approach required no tagging, no custom logs, and no manual instrumentation. Automated discovery began scanning Island's runtime consumption from day one and delivered useful insights within days. The plug-and-play evaluation tied cloud spend directly to business outcomes, giving Island accurate cost per customer, cost per feature, reliable allocation of shared infrastructure and data transfer, and a single source of truth for customer-level cloud economics.
Results
- True cost-per-customer visibility across a complex multi-tenant environment.
- Better pricing and margin decisions through feature- and customer-level insights.
- Cost transparency without the operational burden of tagging or manual cost modeling.
- Stronger alignment across engineering, product, and GTM teams from a shared cost source.
You can't tag a customer in a multi-tenant environment. Attribute™ finally shows us what each customer costs and what's driving those costs.
Omri Cohen, Director of Engineering, Platform
Cost transparency at scale
Island scaled rapidly to hundreds of enterprise customers on a complex multi-tenant cloud foundation. Understanding unit economics was critical from day one. But the team lacked clarity on customer-level margins, expensive features, and unexpected usage patterns. That limited their ability to support pricing, growth modeling, and GTM decisions. Billing data was available, but it couldn't reveal what was actually driving costs at the application layer.
Why traditional tools and tagging fell short
Island's AWS footprint includes heavy use of shared resources such as EKS, RDS, DynamoDB, and significant AZ-to-AZ data transfer. Allocating these shared costs accurately in a multi-tenant environment proved effectively impossible with native cloud tools and third-party platforms. They surfaced bills and charts but couldn't answer the core questions: What does each customer really cost? Which features are expensive to run? Where is high-cost usage coming from? Tagging added heavy setup and maintenance and still couldn't capture customer-level consumption reliably.
FinOps without tagging
Attribute™'s approach resonated immediately. No tagging, no custom logs, and no manual instrumentation were required. Automated discovery began scanning Island's runtime consumption from day one and produced useful insights within days. The evaluation was fast and truly plug-and-play, tying cloud spend directly to business outcomes.
Granular insights, zero overhead
With Attribute™, Island gained accurate cost per customer, cost per feature visibility, reliable allocation of shared infrastructure and data transfer, and a single source of truth for customer-level cloud economics. The platform delivered trusted cost metering without adding operational overhead, revealing exactly where to focus and where savings opportunities existed.
Outcomes across the business
Island can now see what each customer actually costs, even in a complex multi-tenant environment. Feature-level and customer-level insights support smarter pricing and more accurate growth modeling. Engineering, product, and GTM teams operate from a shared, trusted cost source, eliminating the operational burden of tagging or manual cost modeling.
See how Attribute™ reveals the hidden profit in your cloud spend
Explore how Attribute™ delivers runtime cost attribution without tagging, so teams can understand cost per workload, service, and customer.
More customer stories
Turning cloud costs into team action at Hippo
- Minutes
- Time to integrate Attribute™ with AWS
- Business unit
- Level of cost accountability achieved
Claroty unlocks precise customer cost attribution with Attribute™
- 1,000+
- Customers protected worldwide
- Days
- Time to first granular cost reports
- Zero
- Disruption to operations during deployment
SaaS Leader
How Customer-Level Cost Attribution Enables Value-Based AI Pricing
- $1.3M
- in negative-margin revenue surfaced
- ~360
- unprofitable accounts identified
- $1.3M
- in aggregate losses surfaced
Salt Security standardizes COGS measurement to optimize margins and pricing
- 1
- Source of truth for COGS
- 1
- Standardized source of truth for COGS across CFO and DevOps
- 0
- Code or tagging changes required to integrate Attribute™
PropertyGuru turns cloud cost chaos into engineering ownership
- Minutes
- to decode shared service bills (down from hours)
- 32M+
- Monthly property seekers supported
- 2 weeks
- From deployment to actionable insights
From flying blind on cloud costs to product margin visibility
- $46K
- Monthly cloud spend eliminated
- $46K
- Monthly spend eliminated
- $63K → $17K
- Monthly cost reduction for one service
Comprehensive Cloud Cost Visibility with Zero Tagging
- Zero
- Tags required for full cost visibility
- Zero
- Tags required for cost allocation
- Real-time
- Service-level cost visibility
Finlex cuts cloud costs 50% and ships production AI with DoiT
- Over 65%
- reduction in cloud infrastructure costs from 2024 - present
- 40%
- cost savings achieved through improved visibility and efficient AI architecture
Turning cloud costs into team action at Hippo
- Minutes
- Time to integrate Attribute™ with AWS
- Business unit
- Level of cost accountability achieved
Claroty unlocks precise customer cost attribution with Attribute™
- 1,000+
- Customers protected worldwide
- Days
- Time to first granular cost reports
- Zero
- Disruption to operations during deployment
SaaS Leader
How Customer-Level Cost Attribution Enables Value-Based AI Pricing
- $1.3M
- in negative-margin revenue surfaced
- ~360
- unprofitable accounts identified
- $1.3M
- in aggregate losses surfaced
Salt Security standardizes COGS measurement to optimize margins and pricing
- 1
- Source of truth for COGS
- 1
- Standardized source of truth for COGS across CFO and DevOps
- 0
- Code or tagging changes required to integrate Attribute™
PropertyGuru turns cloud cost chaos into engineering ownership
- Minutes
- to decode shared service bills (down from hours)
- 32M+
- Monthly property seekers supported
- 2 weeks
- From deployment to actionable insights
From flying blind on cloud costs to product margin visibility
- $46K
- Monthly cloud spend eliminated
- $46K
- Monthly spend eliminated
- $63K → $17K
- Monthly cost reduction for one service
Comprehensive Cloud Cost Visibility with Zero Tagging
- Zero
- Tags required for full cost visibility
- Zero
- Tags required for cost allocation
- Real-time
- Service-level cost visibility
What they say
DoiT gave us the confidence to move from experimentation to production. They helped us understand the right way to build AI for the real world.
Milad Rezazadeh, CTO
Attribute™'s cost grouping technology took our cost visibility and allocation to a whole new level. Now, our teams are fully accountable for their budgets, significantly improving our cloud efficiency and helping us minimize unnecessary costs.
Eli Zilbershtein, Head of DevOps, Hippo
You can't tag a customer in a multi-tenant environment. Attribute™ finally shows us what each customer costs and what's driving those costs.
Omri Cohen, Director of Engineering, Platform
Attribute™'s data is truly unmatched. No other solution on the market could deliver the precise customer cost and usage profiles we needed in such a complex infrastructure. Within weeks, the data from Attribute™ transformed our understanding of cost structures, influencing key strategic decisions in pricing, renegotiations, and market positioning.
Jonathan Langer, COO, Claroty
Attribute™ simplified tracking customer costs in our multi-tenant environments. Customer cost measurement is now clear and standardized, and finance gets the business context they need. Integration was quick and required no changes.
Kfir Lippmann, CFO, Salt Security
Attribute™ translates complex cloud bills into actionable, business-centric insights that empower our engineering teams to take true ownership of their costs.
Balamurugan Mohandossgandhi, Head of IT and Infrastructure, PropertyGuru
This has let us get a better idea of what our cost of goods sold really is. It's not every day you come across something that delivers value as quickly as yours did for us. I was seeing useful insights inside the POC, and we had only deployed it to a couple of real clusters.
Jason Moore, Principal DevOps Engineer, Accrete AI
Eliminating the need to tag thousands of resources has freed up my team and we've invested our efforts in enhancing our platform significantly.
Ziv Sivan, VP of Engineering
PerfectScale by DoiT has become an important part of how we optimize Kubernetes at scale at OneFootball. It gives our platform team the visibility, automation, resiliency insights, and confidence we need to balance cost efficiency with production readiness, especially as we prepare for major global football moments like the 2026 FIFA World Cup.
Andrea Benfatto, Platform/Cloud Runtime Engineering Manager
Cloudflow's new RDS End of Life alerts have allowed us to be more proactive on keeping our database instances up-to-date. The new solution gives us internal visibility ahead of time so that we can prepare for upgrades, instead of having to upgrade under pressure while incurring extended support costs.
Jon Fairbanks, Site Reliability Engineering Manager
PerfectScale cut 40% off our total EKS spend, and the automations handle what used to take our team 20 hours a month. Now we spend that time on reliability and performance instead of chasing cost metrics.
Caio Cristo, Director of Infrastructure/SRE
What I really like about DoiT's approach is that you're very hands-on and proactive. Satyam would ping me a few times a sprint, letting me know about the most current features, checking in on how things are going. When we are going through a peak time, that proactiveness makes a real difference. Satyam always comes through whenever we need support and helps us leverage the right experts to get us where we need to be.
Chiamaka Ibeme, Engineering Manager, Platform
SELECT has made important cost data readily accessible. I will often pull it up during engineering design reviews so we can quickly evaluate cost impact and projections and factor that into our design decisions.
Douglas Zickuhr, Senior Data Platform Engineer at Personio
Your cloud bill shouldn't be a mystery
Let us show you what ships this week.