Pegasystems bets on outcome-based AI pricing to curb costs
Pegasystems, a US software company working with big banks, is betting on an outcome-based pricing model for AI.
The goal? To keep costs in check as companies move from testing AI to actually using it at scale.
It points out that old-school token-based pricing can end up being 10 to 20 times more expensive than smarter, workflow-driven setups.
Pegasystems uses Blueprint to plan workflows
To make AI spending more predictable, Pegasystems uses its Blueprint platform to plan out efficient workflows and relies on smaller, task-focused AI agents instead of big autonomous systems.
Over half its global developers are based in India (1,966 employees total in the country) who are helping balance cost and efficiency.
CTO Don Schuerman sums it up: it's all about making sure businesses get real value from their AI investments without breaking the bank.