Anthropic launches new reporting tools to help enterprises see what their AI spending buys
Anthropic released a set of reporting tools that let enterprises view team output, token spending, and workflow bottlenecks by date range, along with improvement suggestions, and by default does not use data for model training. Anthropic also introduced shared team budgets to manage token spending. Jellyfish data on 276,000 customers shows that tools based on Anthropic models account for nearly one-third of committed code changes, with related spending growing 10-fold since the start of the year, about 2% of total engineering costs.
Anthropic released a set of reporting tools that let enterprises view team output, token spending, and workflow bottlenecks by date range, along with improvement suggestions, and by default does not use data for model training. Anthropic also introduced shared team budgets to manage token spending. Jellyfish data on 276,000 customers shows that tools based on Anthropic models account for nearly one-third of committed code changes, with related spending growing 10-fold since the start of the year
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