Granular spend analytics
See AI cost broken down by model, agent, workflow, team, and business unit. Know exactly where every dollar goes — in real time, not after the invoice.
Growth with AI
AI Spend and Value Management
Enterprise AI spend is growing 3-5x year over year, but most teams can only see total cost — not which investments are generating value, which are eroding margin, and which should be cut. Econa AI closes the gap between spend visibility and value accountability.
~$486k
labor value generated
410%
return on AI spend
~$122k
digital cost tracked
The challenge
The Problem
AI budgets are expanding rapidly, but finance teams are flying blind. Existing observability tools show tokens, runs, and cost — but they can't answer the question leadership actually asks: "What did we get for that spend?"
Spend is visible at the API or provider level, but value is invisible — no one can connect cost to business value
Finance, Ops, and Product teams each use different tools and arrive at different numbers for the same investment
High adoption is celebrated, but no one measures whether usage translates to measurable business impact
Cost spikes are discovered on the invoice, not in real time — by then the damage is done
Budget renewal conversations become defensive because there's no proof of return, only proof of spend
The solution
How Econa Helps
Econa AI's Foundation connects every AI cost source into a unified spend view, while Economics translates that spend into labor value, margin, and measurable return. The result: one number that tells leadership whether AI is paying off — by workflow, team, and model.
Cost-to-outcome mapping
Connect each dollar spent to the tasks completed, hours replaced, and business value generated. Transform raw cost data into a value story.
Value by workflow and model
Compare measurable return across different AI tools, providers, and workflows. Surface the winners and cut the underperformers.
Spend anomaly detection
Catch cost spikes, runaway workflows, and provider price changes in real time — before they compound into budget overruns.
How it works
Three Steps
1
Unify all spend data
Foundation ingests cost data from every AI provider, model, and workflow into a single economic system.
2
Map cost to outcomes
Economics connects each dollar to the tasks completed, hours replaced, and business value generated.
3
Prove value to leadership
Generate board-ready reports showing return on AI spend — by team, workflow, and business unit.
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