Spend

the spend section gives you real time visibility into how usage translates into cost across your organization all data in this section is derived directly from requests flowing through amberflo and priced using your configured or default model rates there is no delay, no estimation, and no dependency on cloud billing exports ai spend is designed to answer two fundamental questions how much are we spending right now? where is that spend coming from? the ai spend page provides a high level overview of ai costs across workloads and customers so you can quickly understand how usage is impacting your business use this page to track month to date, quarter to date, and year to date spend identify which workloads generate the most cost monitor which workloads are trending up or down understand which customers drive the most spend detect unusual changes in spending patterns this page is intended to provide immediate situational awareness for teams, especially those operating ai powered products spend overview the spend overview page provides a high level snapshot of how costs are distributed across workloads and customers all data shown on this page is derived from actual usage and automatically rated using model pricing as soon as requests are processed through amberflo, the resulting usage and cost data becomes visible here spend overview (mtd, qtd, ytd) at the top of the page you will see three key spend metrics spend mtd – total spend for the current month spend qtd – total spend for the current quarter spend ytd – total spend for the current year each card includes the total spend for the selected period a trend indicator showing how spend is changing compared to the previous period these metrics provide a quick answer to the question how much are we currently spending on ai? time range and scope all data on this page is scoped to the selected time range, controlled by the date selector available presets include week to date month to date quarter to date last 7 days last 14 days last 30 days you can also select a custom date range changing the selected range updates all spend calculations and trend indicators on the page workload spend insights workloads represent the internal unit used to attribute usage and cost a workload may represent an application a product feature a team a service any logical unit of usage the workload section highlights where costs are concentrated and how those costs are changing top spend by workload this view shows the workloads generating the highest total spend for the selected time range this helps you quickly identify the applications or services driving the most cost where optimization efforts may have the greatest impact which parts of your product rely most heavily on ai top trending workloads trending workloads are ranked based on percentage change in spend during the selected time period this can highlight workloads where costs are increasing rapidly due to growing usage decreasing due to optimization or reduced activity trending analysis is useful for spotting sudden changes in behavior that may require investigation customer spend insights if your usage is associated with customers, amberflo can attribute usage and cost directly to them this allows you to understand how costs align with customer activity and billing top spend by customer this view highlights the customers responsible for the largest share of spend during the selected timeframe this helps you understand which customers generate the most ai usage where infrastructure costs are concentrated which accounts may require pricing adjustments or optimization top trending customers trending customers are ranked based on percentage change in spend over the selected time period this helps identify customers whose ai usage is growing rapidly sudden changes in usage behavior accounts that may require monitoring or follow up how this page is meant to be used the ai spend overview page is designed to provide a fast operational snapshot of cost activity use it to monitor overall spending detect sudden changes in workload activity understand which customers or services drive cost identify where deeper investigation may be needed from this page, teams can quickly determine whether ai usage patterns are behaving as expected or if further analysis is required