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QMENTA Cuts Cloud Costs 22% While Scaling AI

DoiT's FinOps guidance, architecture reviews, and Google Cloud optimizations help QMENTA process millions of medical images efficiently.

Meet QMENTA

QMENTA provides a cloud-based system that revolutionizes clinical trials by managing medical images at scale. The company uses AI to anonymize, organize, and standardize thousands of patient images from multiple scanners and hospitals. Their algorithms extract clinical data from each image, providing clinicians with a single source of truth for accurate assessment. This approach improves both the time and cost efficiency of clinical trials while enhancing accuracy through objective quantitative data.

The Challenge

QMENTA needed expert guidance to maximize Google Cloud efficiency while managing compute-intensive AI workloads and massive image storage. The company required cost optimization to pass savings to customers and needed to strengthen security and compliance in a highly regulated healthcare environment.

The Solution

DoiT provided comprehensive cloud optimization through FinOps consultations, architecture reviews, and specialized training. The solution included implementing Committed Use Discounts, optimizing Kubernetes usage, strategizing storage with Google Cloud Autoclass, and enhancing security with identity management and intrusion detection systems.

Results

Achieved 22% reduction in Google Cloud costs within nine months
Gained unlimited access to cloud reliability engineers for faster decision making
Future-proofed infrastructure for 2-3x growth expansion
Enhanced team confidence through specialized cloud training sessions

We expect QMENTA to grow its current size considerably over the next year, which will see our cloud usage increase considerably. Through our work with DoiT we have future-proofed our growth, ensuring that as we scale exponentially, our cloud spend remains firmly under control.
Paulo Rodrigues, CTO and Co-Founder

Controlling costs while maximizing cloud potential

DoiT's Cloud Reliability Engineers conducted comprehensive FinOps consultations, reviewing QMENTA's infrastructure to provide actionable optimization recommendations. Key initiatives included implementing Google Cloud Committed Use Discounts with careful analysis to ensure appropriate commitments, and developing commitment automation strategies for continuous best-available pricing. QMENTA leveraged DoiT's Cloud Analytics dashboards for enhanced visibility and control of cloud expenditure, enabling the team to identify overspending areas and make targeted adjustments for significant savings.

Optimizing computing and data storage

DoiT provided specialized Kubernetes training sessions to help QMENTA optimize Google Kubernetes Engine usage for their AI workloads. The team learned to scale usage up and down according to demand, reducing GKE nodes for memory-light tasks while scaling up for high-performance requirements. For storage optimization, DoiT helped strategize the best approach to storing millions of medical images, balancing accessibility with costs. QMENTA implemented Google Cloud's Autoclass feature in Cloud Storage to automatically classify images and ensure optimal storage pricing for each file type.

Strengthening cloud security for patient data

DoiT conducted identity and access management workshops to familiarize QMENTA with industry best practices, including effective user group management for streamlined access control. The company received recommendations for cost-effective implementation of Google Cloud Intrusion Detection System, starting with test projects before production deployment. QMENTA is now working with DoiT to explore optimal usage of Google Cloud Security Command Center to further enhance their security posture while managing costs effectively.

Future-proofing for exponential growth

Having completed fundraising and validated their product, QMENTA is scaling customers and users, which will significantly increase stored and processed images. The optimization work with DoiT has prepared the company for this expansion. As Paulo Rodrigues noted: 'We expect QMENTA to grow to two or three times its current size over the next year. Through our work with DoiT, we have future-proofed our growth, ensuring that as we scale exponentially, our cloud spend remains firmly under control.'

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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

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