Ramp is building AI spend management that pulls token-level usage data from AI providers and attributes it to teams/projects so finance can see where costs come from.
AI bills are opaque and spiky; without attribution, orgs either clamp down indiscriminately or overspend with no ROI signal.
Tokenmaxxing needs FinOps: track tokens by user/app/model, set budgets and alerts, and connect usage to business outcomes—not vanity token counts.
The piece frames token spend as a fast-growing, hard-to-track cost—and positions token-level visibility and allocation as the missing layer for enterprise control.
langchain-ai/langgraph
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BerriAI/litellm
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langfuse/langfuse
Open-source LLM engineering platform for observability, traces, metrics, evals, prompt management, datasets, and playground workflows.
Leaked internal audio, reported by IT Pro via 404 Media, shows Accenture telling staff to stop burning AI tokens on low-value work like turning PDFs into slide decks, as its agentic-AI lead flags a sharp jump in token spend.
KPMG’s Q2 AI Pulse (204 US leaders at $1B+ firms) finds twice as many companies now running fleets of coordinated agents — up to 18% from 9% — yet only 26% can see in real time what AI at scale actually costs them.
Ramp closed a $750M round at a $44B valuation and is launching AI token spend management, procurement agents, and accounting agents on top of $1B+ annualized revenue and 70,000+ customers.