DoiT Becomes Founding Member of the Tokenomics Foundation, Helping Define the Standard for AI Cost Attribution

DoiT's Attribute™ product, which traces every token, inference and training run to the team, product and customer that drove it, aligns with the Tokenomics Foundation's mission to define how the industry tracks and governs AI spend

SANTA CLARA, Calif., Aug. 4, 2026 /PRNewswire/ -- DoiT, the company behind Cloud Intelligence™ and its AI cost product Attribute™, today announced that it has become a founding member of the Tokenomics Foundation to help establish open standards, benchmarks and best practices for the economics of AI infrastructure. As a founding member, DoiT will help define how the industry attributes and governs token, model and GPU spend, work already reflected in Attribute, which measures AI consumption at the kernel and traces every token, model request and GPU cycle back to the customer, feature and agent responsible for it.

Amit Kinha, Field CTO at DoiT, will be a governing Board member of the Tokenomics Foundation, embedding the practitioner and engineering perspective that shaped Attribute using the Foundation's industry standards.

The industry has arrived at a point where tokens have become an atomic working unit of technology spend. As enterprises move generative and agentic AI from early pilots into production, AI has grown into one of the largest and fastest-moving lines on the technology budget, while the discipline needed to measure and govern that spend has lagged behind. Industry analysts now forecast more than one trillion dollars in AI infrastructure investment through 2027, with the inference market alone expected to grow from roughly 106 billion dollars in 2025 to 255 billion dollars by 2030.

For the teams living with that spend, the gap is already acute. In the FinOps Foundation's most recent State of FinOps research, 98 percent of practitioners reported that they now manage AI spend, up from 31 percent two years earlier, and they named granular visibility into tokens, model requests and GPU usage as their most requested capability. DoiT's own survey of 500 executives at large enterprises found that only 15 percent of respondents could calculate the return on their AI investment without significant bottlenecks.

The reason those costs stay hidden is architectural. The dynamic nature of LLM gateways, shared GPU clusters and AI agents makes tagging effectively impossible. A managed model serves many customers at once, a shared GPU cluster runs several products in parallel and every billing tool sees the gateway as the consumer, collapsing requests from agents, humans and integrations into a single stream. No tag survives the hop through a gateway, and no SDK can see inside a shared GPU.

Attribute was built for exactly that environment. DoiT spent more than a decade helping over 4,500 customers untangle shared infrastructure and move from tag-based allocation toward consumption-based attribution. Now, Attribute extends that tagless model to the AI layer by deploying a lightweight eBPF sensor that observes actual consumption inside the operating system. Attribute maps every token, model request and GPU cycle to the process, workload, customer and agent that caused it, then joining that runtime data with provider billing from Anthropic, OpenAI, Google Gemini and AWS Bedrock. The sensor installs in about fifteen minutes and produces per-customer, per-feature and per-agent token economics the same day, with no SDK, no tagging policy and no code changes. Attribute became generally available in July 2026.

"Every organization running AI is now asking the same question they once asked about cloud: what is this actually costing me, and what am I getting for it? Tokenomics is the discipline that answers it. FinOps gave us a shared language for cloud spend, and the Tokenomics Foundation does the same for tokens, models and GPU cycles. DoiT is proud to be a founding member, and I'm honored to help steer this work as a member of the Governing Board," said Amit Kinha, Field CTO at DoiT.

The formation of the Tokenomics Foundation and DoiT's place among its founding members reflect two sides of the same development. The launch of the Foundation validates token-level economics as a crucial discipline rather than cloud cost management under a new name, and that the industry needs shared standards to practice it. DoiT's founding seat reflects the maturity of the measurement layer it brings to that work, with Attribute delivering what the Foundation is setting out to standardize.

"Bringing together builders and operators is critical to defining open standards that directly connect AI usage to business value. We're excited to welcome DoiT alongside its industry peers to help shape best practices in this emerging space. Their perspective will be helpful in accelerating the benchmarks and frameworks needed to make AI systems more measurable, accountable, and economically efficient at scale," said J.R. Storment, Executive Director of the Tokenomics Foundation.

As a founding member, DoiT will help shape the benchmarks, definitions and best practices the Tokenomics Foundation publishes, bringing the runtime measurement experience behind Attribute to the table as the standards take form. Organizations that want to see token-level attribution in their own environment can request a demonstration at doit.com/demo/attribute.

About DoiT

DoiT keeps your cloud infrastructure always at its best. The Cloud Intelligence™ platform combines AI-driven FinOps automation with Forward Deployed Engineers who work alongside customer teams to ship real savings rather than recommendations alone. Across AWS, Google Cloud and Azure, DoiT manages more than 20 billion dollars in cloud spend for 4,500 customers in 70+ countries, with a 99.7 percent average customer satisfaction score. The platform covers AI tokenomics, Kubernetes, commitment management, data platform optimization and FinOps automation. To learn more, visit doit.com.

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SOURCE DoiT