For the engineering manager staring at a Monday-morning AWS bill that grew 18 percent over the weekend, the hardest part is rarely spotting the overspend. It is figuring out which Kubernetes namespace, which forgotten reserved instance, or which Datadog commitment is responsible, and then convincing a sprint team to actually fix it. DoiT International, the Santa Clara company that has spent more than a decade embedding itself between hyperscalers and their customers, is betting that the next phase of FinOps belongs to whoever can shorten that gap between a cost alert and a closed Jira ticket.
DoiT calls its approach an intent-aware FinOps platform, one that pushes past dashboards into what it describes as actionable engineering tasks for AWS, Google Cloud, and Azure [DoiT]. The pitch resonates with a specific patient population in this story: cloud-native engineering organizations large enough to feel the pain of waste, but not large enough to staff a dedicated FinOps team. Today, the standard of care for those teams is a patchwork. Most run native cloud cost tools (AWS Cost Explorer, GCP's billing console), layered with a third-party analytics product such as Apptio Cloudability or CloudHealth by VMware, and supplemented by a managed-services partner that handles reserved-instance purchasing on the side. The result is visibility without velocity. Reports get generated, recommendations get filed, and engineers keep shipping features.
The bet
DoiT's wedge is to package the analytics, the automation, and the human expertise into a single subscription that sits next to a customer's cloud accounts. The Cloud Intelligence platform handles cost management, optimization, governance, and what the company calls productivity tooling [DoiT]. Underneath, it automates commitment management for AWS and Google Cloud (reserved instances, committed use discounts), attributes Kubernetes spend down to the workload, and now pulls in third-party SaaS commitments such as Datadog, where customers can self-service their renewal terms inside DoiT's console [DoiT]. Against Mission Cloud, which leans on managed services, DoiT positions itself as the option that lets internal teams keep control while still getting embedded FinOps guidance [DoiT].
That positioning has produced a meaningful book of business. The company reported $86.8 million in revenue in 2025, with 789 employees and more than 3,000 customers across over 70 countries. Its careers site separately describes a team of roughly 700 working fully remotely from 40-plus nations [DoiT Careers]. Pricing is published openly, a relative rarity in the category, and spans cost management, Kubernetes optimization, Snowflake performance, and AI accelerator workloads [DoiT].
Why it could be big
Cloud spend is one of the few enterprise line items that has kept growing through every budget cycle of the past three years, and the FinOps Foundation's practitioner community has expanded alongside it. DoiT is a member of that ecosystem and frames its platform in the foundation's vocabulary [FinOps.org]. Investors have backed the thesis with real capital. The company has raised roughly $100 million in disclosed funding, with Bain Capital, Charlesbank, and Deutsche Bank on the cap table [Tracxn]. More recently, DoiT established a $250 million fund earmarked for acquisitions in AI-driven cloud operations, a signal that the company intends to consolidate adjacent tooling rather than wait for the market to do it [Channel Futures].
That M&A posture matters because the next wave of cloud cost growth is going to come from AI workloads, where GPU reservations, inference traffic, and model-training jobs behave very differently from steady-state web infrastructure. A FinOps vendor that can absorb specialist tooling for those workloads, while keeping its existing footprint across AWS, Google Cloud, and Azure, has a credible path to becoming the default control plane for an engineering org's cloud bill.
The team and traction
DoiT was founded in 2011 by Vadim Solovey and Yoav Toussia-Cohen, and the two have run the company in a co-CEO structure, with Solovey also serving as CTO [Craft.co]. Solovey has been publicly profiled as a Google Cloud Rockstar, reflecting the company's deep partnership posture with Google [CRN]. The leadership bench has been built out for the platform phase: John Purcell joined as Chief Product Officer, a role the company tied explicitly to its evolution toward developer and DevOps tooling [DoiT]. Amit Kinha serves as Field CTO. Open roles on the Greenhouse board, including a SaaS Account Executive and a GKE-focused Cloud Engineer, suggest continued investment in both go-to-market and Google Cloud depth.
2025 Revenue ($M) | 86.8 | $M
Disclosed Funding ($M) | 100 | $M
M&A Fund ($M) | 250 | $M
The honest counterfactual
The bears in this category will point out that FinOps is crowded and consolidating. Apptio is now inside IBM, CloudHealth sits inside Broadcom's VMware, Spot belongs to NetApp, and Vantage has built a fast-growing independent business with a developer-friendly UX. Any one of them can claim multi-cloud coverage, and the largest enterprises increasingly want a single procurement relationship. The bulls' answer, supported by DoiT's reported revenue scale and customer count, is that DoiT has spent more than a decade building a hybrid model (software plus embedded human expertise plus reseller economics with the hyperscalers) that pure-play software vendors cannot easily replicate, and that the $250 million acquisition fund gives it the capital to fold in AI-era tooling before the incumbents do [Channel Futures].
What to watch
The next twelve months should make the strategy legible. Watch for the first announced acquisition out of the $250 million fund, which will signal where DoiT thinks the AI-cloud-cost frontier actually sits (GPU scheduling, inference observability, or model-cost attribution are the obvious candidates). Watch the pace of platform expansion beyond Datadog into other large SaaS commitments. And watch whether the co-CEO structure produces a clean external narrative as the company approaches the scale where a late-stage round, or an eventual public listing, becomes a realistic conversation.
The disease state here is cloud waste, the patient population is the engineering team that owns the bill, and the standard of care is still mostly dashboards and quarterly reviews. DoiT is arguing that those patients deserve something closer to a treatment plan. The evidence so far suggests the argument is landing.