Overview

Generative AI is transforming how businesses operate and innovate. Yet as organizations adopt AI at scale, they encounter complexities—unpredictable usage patterns, fragmented pipelines, and fluctuating performance requirements—that most traditional cost-management tools simply can’t handle. These limitations make it difficult to forecast budgets, manage cross-functional collaboration, and confidently align AI investments to business outcomes.

Pay-i solves these challenges with a single, purpose-built FinOps platform that unifies cost transparency, usage analytics, and operational governance across Azure OpenAI and other major GenAI model providers. By tracking the full economics of AI workflows—down to the per-inference level—Pay-i empowers finance, product, and engineering teams to optimize performance, control spend, and scale Generative AI responsibly.

Key Capabilities

Single Pane of Glass for GenAI
Get a unified view of AI workloads across Azure OpenAI and other environments. From one dashboard, track KPIs, costs, and performance metrics for each AI-driven experience.
Unit Economics for GenAI
Move beyond “cost per inference” to understand full AI workflow cost and margin. Drill down per model and per integration to tie spend directly to specific business outcomes.
Granular Performance and Latency Metrics
Capture real-time data on latency, throughput, and model success rates. Diagnose bottlenecks and measure how performance impacts user satisfaction and cost.
Detailed Cost Analysis
Access comprehensive breakdowns of infrastructure usage, provider billing, data transfer, and GPU consumption. Identify hidden cost drivers and accurately forecast budgets.
Native Integrations with Leading AI Providers
Connect seamlessly to Azure OpenAI and other major GenAI models. Streamline provisioning, billing, and attribution so you can easily adopt new AI capabilities without losing sight of spend.

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