DoiT Introduces Attribute for AI Spend Attribution Without Instrumentation

DoiT has launched Attribute, a tool designed to attribute AI costs across tokens, GPU usage, and model requests with no instrumentation required. The product is now generally available and was announced in a press release from the company.

Attribute uses a lightweight eBPF sensor that installs in about fifteen minutes to measure consumption directly at the operating system kernel. The sensor traces GPU, CPU, memory, and network usage per process, container, and request, linking each to cost data from managed model APIs such as Anthropic, OpenAI, Google Gemini, and AWS Bedrock.

The system automatically splits input, output, cached, and reasoning tokens to generate detailed cost data per customer, feature, and agent. This enables teams to see the cost of serving each customer and measure gross margins and unit economics for AI features without engineering overhead.

DoiT stated that Attribute extends the same attribution model to Kubernetes clusters, databases, storage, and networking resources, providing continuous cost visibility across enterprise infrastructure.