Bring cost control to your AI workloads
AI is the fastest-growing line on your Azure bill and the least governed. Turbo360 puts Azure OpenAI and AI Foundry token spend under the same FinOps discipline as the rest of your cloud, so every token behind every AI feature has an owner.
The problem, solved
What teams come to us with
Each pain has a concrete outcome in Turbo360. No waiting on engineering.
AI spend lands with no owner
Allocate every token to an owner
Slice AI cost by model, project, team, or business application, so the spend behind each AI feature is accountable like any other line.
Token costs spike overnight
Catch AI overspend the day it starts
Machine-learned baselines flag a runaway prompt loop or a jump in token usage in real time, and route the alert to the team that owns the workload.
AI cost is seen in isolation
See AI cost in the whole application picture
Group AI spend with the compute, storage, and services it runs alongside, so you see the full cost of an application, not just its AI line.
Two ways to look
Read AI cost across the org, or
inside a single application
The same AI spend answers two different questions. Look horizontally to see AI cost across every team, or drop into one
application and see its AI line sitting alongside the compute, storage, and networking it runs with.
The horizontal view in the product: daily cost across every AI service in one estate,
stacked so you see which service is driving the bill.
The horizontal view
AI cost across the whole organization, sliced by team, project, or model, so you can see where AI spend is concentrated and which teams are driving it.
The vertical view
Drop into one business application and see its AI tokens costed next to compute, storage, and networking, so AI is one line in the full picture, not a bill on its own.
One source, both lenses
AI spend is grouped the same way as the rest of your estate, so switching between the org-wide roll-up and a single application never means a second tool or a fresh export.
Cost review
See exactly what changed in your AI
spend, period over period
Put two periods side by side and Turbo360 shows the cost difference on every line, so a jump or a drop stands out at a glance. Review by meter subcategory as shown here, or by subscription, resource group, resource, or tags, whichever way your AI spend is organized.
AI inventory
Every AI resource in one list, one
click from the detail
See all your Azure AI resources in a single inventory, ranked by cost. Open any one to drill into its spend and usage, from characters translated to tokens and requests, so you know what each resource is doing for the money.
Azure OpenAI · by meter
Break Azure OpenAI cost down to
the token meter
Group Azure OpenAI spend by meter to see exactly which tokens cost you: input, output, and cached, split per model. When you move a workload from one model to another, the shift shows up in the mix, so you always know what you are paying for.
Explain with AI
Turn a wall of cost data into plain-
English insight
Anywhere you see a chart or a bill you do not fully follow, click Explain with AI. Turbo360 reads the data in front of you and returns an executive summary, the top cost drivers, and the risks worth acting on, in language anyone on the team can read.
Monitoring
Monitor all your AI cost
with one budget
Use the group budget to wrap every bit of AI usage in a single, easy-to-manage budget. It works in both views: roll all your AI
services up horizontally, or scope the same budget down to one application, and let alerts do the watching.
One budget, every AI service
The group budget spans all your AI usage in the horizontal view, so translator, speech, and model spend roll up into a single number you manage in one place.
Or scope it to one application
Point the same budget at a single business application to watch its AI spend in the vertical view, alongside the compute and storage it runs with.
Alerts route to the owner
Set the thresholds once and Turbo360 notifies the team that owns the spend before the budget is breached, not after the invoice lands.
AI anomaly detection
Catch a runaway AI bill
the day it spikes
Turbo360 learns what normal looks like for every AI meter and resource, then watches daily. When AI spend breaks its pattern, the point turns red, an AI agent checks it is real, and the owner hears about it before the invoice.
Learns your AI baseline
Machine-learned baselines are built per meter, resource, and subscription, so normal is defined for each AI workload rather than one blanket threshold.
Flags the spike as it happens
Actual AI cost is checked against the baseline every day, so an unexpected jump is caught the day it starts and marked on the chart in red.
Verifies, then routes to the owner
An AI agent confirms the spike is real, not noise, then alerts the team that owns the workload with the dollar impact attached.
Real-time monitoring
Go beyond the bill with near real-
time token monitoring
Billing data lags by hours, sometimes a day, so a cost spike is already spent by the time it shows on the invoice. To protect against that, the Business Applications module watches the metric and log data instead, so you catch a runaway workload as it happens, at the resource level.
Metrics, not the invoice
Billing data arrives after the fact. Metric data is near real-time, so token usage, blocked calls, and model availability are visible as they happen, not hours later.
Thresholds on token usage
Set warning and error thresholds on Total Tokens and the metrics around it, so an unusual burst of usage trips an alert in minutes rather than at month end.
Metrics and log queries
Combine Azure Monitor metrics with Log Analytics queries in one place, for granular, near real-time signals that pinpoint the problem sooner.
Token usage visibility
Surface every token transaction to
the people who need it
Azure and OpenTelemetry frameworks already emit token usage to Application Insights. Turbo360 reads it from your logs through Business Applications or Business Activity Monitoring and surfaces those token transactions to the teams who need them, in views built for the business or for operations.
Already in your logs
Azure and OpenTelemetry frameworks emit token usage to Application Insights. Turbo360 reads it straight from your logs, so there is nothing extra to instrument.
Views for each audience
Surface token transactions through Business Applications or Business Activity Monitoring, and build business-friendly or operations-friendly views for the people who need to see them.
Query for heavy usage
Write queries that pick out transactions with heavy token usage, so you can investigate the calls driving cost and fix them at the source.
End-to-end context
See token usage inside the wider transaction with end-to-end tracking and observability, not as a number stripped of the request it belongs to.
Trusted by leading Azure service provider worldwide
“Turbo360 gives our MSP partners clear visibility into Azure costs, with smarter alerts and proactive management they can pass straight to their customers.”
James Reed
Azure Sales Manager
“We had to consolidate data manually, and the reports were always a snapshot—never real-time. Moreover, our customers couldn’t access their own data, making it hard for them to understand their costs.”
Alex Tilgenkamp
Cloud Architect
FAQ
Common questions
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What can I ask the FinOps agent?
Ask why spend changed, what a team or application costs this period, where waste is hiding, or which optimization to do first. The agent answers from your live environment.
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Do the agents take action automatically?
Agents recommend and rank actions with the dollar impact made clear. You stay in control and apply the ones you approve.
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How are recommendations ranked?
By estimated dollar impact, so your team starts with the moves that save the most, with the trade-off on performance shown for each.
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Is my Azure data used to train external models?
No. Turbo360 connects with read-only access and is independently audited against SOC 2 Type II and ISO 27001.
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