Rippling's AI Spend Console slashes token waste 60%

HR software provider Rippling built AI Spend Console after discovering it was on track to burn 40% of its R&D headcount budget on AI tokens—roughly $50M annually. The tool maps spending by employee/team and flags unproductive usage, like employees defaulting to expensive frontier models for trivial tasks. After negotiating spending caps with providers and implementing an AI gateway that routes prompts to cost-effective models (e.g., Z.ai’s GLM 5.2 at 85% cheaper than frontier models), Rippling cut token costs from 40% to 15% of R&D budget while maintaining usage levels.

Rippling’s solution combines spend tracking with an AI gateway that selects models based on task complexity and cost. The tool now flags users who drive 60% of spending (e.g., one engineer spending $50K/month) and highlights teams whose AI outputs require frequent redoes. Enterprises are adopting similar strategies, balancing frontier models (like SpaceX’s Grok) with cheaper alternatives (GLM 5.2) and third-party gateways. Rippling’s tool integrates with existing gateways but requires its own for full spend governance.