Spend Classification

AI token consumption and session quality data classify spend efficiency, attributing costs to teams and tools.

Business impact

• AI spend efficiency — Measures how effectively AI tokens convert into productive work, reducing waste
• Cost control — Enables identification and reduction of unnecessary spend through accurate classification
• Workflow optimization — Improves process efficiency by highlighting inefficient or redundant AI usage patterns

Data requirements

• AI token usage logs (Numeric) — Track token consumption per session to classify spend efficiency
• Engineering workflow metadata (Structured) — Contextualize token usage with team, tool, and task information for attribution
• Session quality metrics (Numeric) — Assess output quality to determine productive versus wasteful AI usage

AI methods and techniques

• Symbolic AI — Apply rule-based classification to categorize spend tokens by efficiency and context
• Predictive AI — Forecast spend trends and identify potential inefficiencies in AI consumption

AI models and model families

GPT-4o, Claude, Llama