Cost
Optimization.
The same living model that powers AI acceleration also maps infrastructure spend to your architecture. Cost attribution by service, team, and decision. Commitment optimization. AI token usage tracking. Context-aware recommendations — not just dashboards.
Spend is rarely connected to the systems, teams, and decisions that drive it.
Cloud and infrastructure costs grow with every team, every service, every environment. Optimization happens in spreadsheets, not in the engineering workflow.
AI Usage Analytics
Token spend by model, team, task type, and outcome. Understand which AI usage drives results and which is waste. Track LLM costs across providers with context-aware attribution.
Learn about AI Usage Analytics →Infrastructure Cost Attribution
Cloud spend mapped to services, teams, and architectural decisions — not just accounts. Understand why costs grow, not just that they did. Powered by the same system model.
Learn about Infrastructure Cost Attribution →Measurable ROI
Connect AI tool spend to engineering outcomes — cost per PR, cost per feature, efficiency gains by team. The number your board is asking for, derived from real signals instead of surveys.
Learn about Measurable ROI →Budget & Forecast
Track AI tool and cloud commitments, forecast spend against actuals, and model optimization scenarios. Know where you're headed — and where to adjust — before budget cycles hit.
Learn about Budget & Forecast →Spend connects to the architecture that drives it.
Finance and engineering teams understand infrastructure costs with real context. Optimization is proactive, not reactive.