4mo
to budget zero
at Uber
at Uber
Uber's engineering team burned its entire 2026 AI budget in four months. The COO is now publicly questioning whether the spending is worth it.
— Fortune, May 2026
Token Spend & Insights
Account for every AI token and dollar. Across tools, agents, teams and outcomes.
Your AI spend is everywhere. No one can tell you the true total. Larridin can.
This is the scale
Tokens don't slow down. Neither does your spend.
AI tokens processed since you opened this page
0
↑ 1 billion/sec · Google alone, May 2026
Some out there might call this tokenmaxxing — and there's probably some truth to it.
$6M
unplanned,
in six months
in six months
One healthcare enterprise consumed 1 trillion tokens before finance understood what was driving it.
— Elvex, 2026
78%
of leaders,
blindsided
blindsided
Enterprise AI spend jumped 108% year over year. 78% of IT leaders reported charges they never budgeted for.
— Zylo 2026 SaaS Management Index
Here is how Larridin closes every gap
01 Integration
AI spend comes from six places. No one can tell you the total.
Token usage, seat licenses, cloud model calls, API gateways. They all measure cost differently. Larridin connects to every source and maps them into a single spend model — automatically.
- All sources, one spend model
- No manual exports or spreadsheets
Across every source
$183k
total spend MTD
8
models in use
183
agents running
02 Visibility
Agents are running up costs with no team, no owner, and no budget attached.
Most tools measure human output or agent output. Not both together. Larridin gives you the human and agent split in a single view so every dollar traces back to whoever spent it — and what they produced.
- Human and agent spend in one view
- Every agent traced to an owner
Human + agent, in real time
839
users tracked in real time
183
active agents monitored
27%
of sessions are agents
72%
of variable spend is agent-driven
03 Attribution
Tokenmaxxing without accountability is a budget waiting to break.
Someone will ask what the AI spend produced. You'll need an answer that holds up. Every token traced to a team, an agent, and a use case — then connected to output: velocity gained, hours saved, meetings cut.
- Every token tied to a team and an outcome
- Cost per unit of work, not cost per seat
04 Alerts
Most AI spend problems announce themselves too late.
Larridin flags projected overages, unattributed spend, agent debt, and dormant seats before they turn into renewal surprises or runaway costs.
- Projected overages flagged before quarter close
- Orphaned agents with no owner surfaced
- Dormant seats surfaced before renewal
What a first scan surfaces
18%
of spend unattributed on average across enterprise deployments
47
orphaned agents found on average in first scan
Budget alert
Projected overage
Projects spend per team and flags budgets at risk before the quarter closes.
Attribution gap
Unattributed spend
Surfaces every dollar that hasn't been mapped to a team, agent, or use case.
Agent risk
Agent debt
Flags active agents with no accountable owner before they run unchecked.
Subscription drift
Dormant seats
Identifies enterprise seat licenses unused in the trailing 30 days, ready to reclaim or renegotiate at renewal.
Beyond Spend
Spend is one number. The picture is bigger.
Larridin already measures how broadly your teams use AI, how skillfully they use it, whether it's making them more productive, and how the work itself is changing. Spend is the cost side of that picture. See it next to the rest and you stop asking what AI costs and start seeing what you get for it.
These questions are coming. Have the answers ready.
What are we spending on AI? Who's spending it? Is it working? Someone will ask. Larridin means you don't have to scramble to find out.
Book a Demo