Net Health grew into a multi cloud, multi product company the way most healthcare technology companies do, one acquisition at a time. Each deal brought its own tech stack, its own cloud provider, and its own way of tracking cost. Finout gave the platform team a way to turn that patchwork into a single, governed view of spend, and gave product and finance teams a seat at that view for the first time.
About Net Health
Net Health is a healthcare technology company built on more than 30 years of clinical experience, serving healthcare organizations across rehab therapy, wound care, occupational health, and skilled nursing. Its portfolio has grown largely through acquisition, and today spans close to a dozen specialty software products, some sold standalone and some designed to work together, such as its Optima documentation tool and its Limber outcomes and patient survey platform.
That growth by acquisition is also what shaped Net Health's cloud environment. The company runs primarily on Azure but grew an AWS and GCP footprint overnight through separate acquisitions. Net Health also runs on Anthropic, using Claude across engineering and, increasingly, across the rest of the company.
The Challenge: A Cloud Footprint Shaped by Growth
Before Finout, Net Health's platform team tracked Azure spend manually, pulling from Microsoft's own invoices into Excel. Matt Frederiksen, VP of Platform Engineering, Cloud, described it as a process built around spreadsheets rather than a dedicated cost platform, one that hadn't yet caught up with a multi product portfolio like Net Health's.
- Shared resources had no clean owner. A number of Azure resources, resource groups, and even entire subscriptions were shared across multiple products, with only a rough sense of how to split the cost between them.
- Every acquisition added a new environment. One deal brought a GCP footprint, another grew the AWS footprint overnight, and none of it arrived pre organized for a single, consistent view of spend.
- Product and finance had no self serve view. Forecasting and budget planning for cloud spend individual products was not something the company had in place at all before it built out its FinOps foundation.
None of this showed up as a single dramatic failure. It showed up as a platform team spending real time every month reconstructing, by hand, a picture that should have already existed.
Why Finout?
- Virtual Tags split shared Azure resources by product. No other option gave the team a way to take shared resource groups and subscriptions and assign the cost across the products actually using them.
- Visibility down to the individual resource, which let the platform team catch and investigate cost anomalies, such as recurring storage account overages, instead of finding them after the fact.
- One shared model for platform, product, and finance, replacing three separate ways of looking at the same spend with a single source both engineering and finance could trust.
- An implementation that did not take months. Onboarding Azure, the bulk of Net Health's cloud footprint, was fast, and the team could see and use Virtual Tags and MegaBill almost immediately.
The Solution: One Model for Product, Platform, and Finance
Turning shared Azure resources into product level ownership
Virtual Tags were, in Matt's words, what actually won Finout the business. Net Health had shared resources, resource groups, and subscriptions across Azure with no way to divide the cost between the products using them, a gap the team hadn't found a way to close with Azure's native tools or the other options it evaluated. That structure now feeds Net Health's existing budgeting, forecasting, and monthly true up process, giving product teams a real per product view of cost that did not exist before.
“The virtual tagging in all honesty is what really won the battle for Finout. No one else gave us the ability to come in and take shared resources, shared resource groups, shared subscriptions and appropriately assign the associated costs.”
Matt FrederiksenVP, Platform Engineering, Cloud
Catching cost anomalies before they become a pattern
One of the platform team's favorite uses of Finout has been anomaly detection on storage accounts. A recurring cost overage on the same storage accounts took four rounds of investigation to fully resolve. Each time, Finout surfaced the latest issue so the team could trace it back to its actual cause. Most often, the root cause was an issue with configuration rather than underlying resources.
Turning Anthropic spend into a productivity conversation, not just a bill
Claude has become close to the default interface for how Net Health's engineers get work done. That made Anthropic spend a growing line item that team leaders wanted visibility into, not to police token usage, but to understand who was using AI well and what the rest of the team could learn from them.
“The reporting we get in Finout for our Anthropic usage is exactly the level of detail we need, formatted the way we actually use it day to day.”
Matt FrederiksenVP, Platform Engineering, Cloud
That visibility now feeds real conversations at the engineering leadership level. Teams compare Anthropic usage against what people are actually shipping (story points, tools built, time saved) to identify who is getting outsized value from AI so others can learn from them, and to flag high spend with no output to show for it.
Impact and Results
Real time saved on reconciliation. Matt estimates Virtual Tags save him roughly a business day a month that used to go into manually working through Microsoft's Azure exports. The finance team, which handles the broader monthly true up, estimates a similar gain measured in business days rather than hours.
A recurring anomaly, actually root caused. Four rounds of investigation on storage account overages, tracked and resurfaced by Finout each time, rather than treated as a one off fix.
A forecasting capability that did not exist before. Product owners and BU leaders now have their own view into cost and forecasting, a capability Net Health's FinOps foundation did not support prior to Finout.
Cost visibility that changed how AI usage gets managed. Anthropic spend inside Finout is detailed enough to support real conversations about who is getting value from AI, not just how much it costs.
“We will need that insight from a tool like Finout that is a neutral third party observer to tell us where we're getting the most bang for our buck for our end users' usage.”
Matt FrederiksenVP, Platform Engineering, Cloud
Spotlight
Claude, Through the Finout MCP, as a Daily Interface for Cost Answers
Claude is central enough to how Net Health's platform team works that it has become, in Matt's words, close to the front end for everything, including Finout. The team uses Billy, Finout's AI assistant, for building and troubleshooting dashboards inside the product itself. For quick, text based questions about cost, they increasingly go straight to Claude through the Finout MCP instead, staying inside the tool they already live in rather than opening a separate dashboard.
Looking Ahead
- Bring AWS fully into Finout now that Net Health's renegotiated Azure consumption commitment has cleared the way to prioritize onboarding its AWS footprint.
- Extend self serve visibility to platform engineers, including the SREs and DBAs closest to individual resources, with permissions and scope still to be worked out.
- Deepen the link between Anthropic spend and productivity, as engineering leadership continues to correlate usage with what teams are actually shipping.
- Decide how to allocate Anthropic's per seat enterprise spend the way Azure and AWS cost is already allocated by product and team.
