How do you know the AI caused the improvement?

We measure each team against its own baseline and trend, and isolate AI-touched work — so you see the change, not a vanity number.

Is this accurate enough to act on?

We compare each team only to its own history (never apples-to-oranges) and show the underlying signals, not a black box.

Do you watch individual employees?

No. Everything is measured and reported at team level. No individual scoreboards, and teams are never ranked against each other.

What data do you read — and not read?

We read work items — pull requests, tickets, deals — and their activity history, plus AI usage and billing. We never read the content of your documents, code, or messages, and we never write to your systems.

How fast do we see value?

First baseline in days; a first budget-grade picture inside a month.

Do we rip out our cost or monitoring tools?

No — AIReturn sits on top and answers the one question they don't: did the work get better?

Know what your AI is actually delivering

See if your AI is paying off — and fix what isn't.

AIReturn measures what your teams and AI agents actually produce, the rework they waste, and the return on every AI dollar — across engineering, product, support and sales — so you know where to spend more and what to fix.

See how it works

Return on AI

Last 90 days

3.1×

return on AI spend

AI under management

$1.2M

Wasted on rework

$140K

Recoverable

$92K

How we calculate this

Companies are pouring money into AI. Almost no one can prove it's working.

Only28%

of AI use cases hit their ROI target

— Gartner

74% → 20%

expected AI to grow revenue vs. those who saw it

— Deloitte

78%

of finance leaders can't tie AI spend to outcomes

— CloudZero

What “return on AI” actually means

Your AI ROI, in one picture.

The 3.1× above isn’t a black box. Here’s exactly what it’s made of — in plain language, and every piece links to where you see it in the product.

Every number is measured against your own history — so the ROI is honest, whether it’s positive or not.
See the full methodology

Click a box or lever above to change this panel

For the AI leader

A map of who’s efficient and who’s burning.

Every team plotted by AI cost per result against rework — green pays off, red burns. Each team is measured against its own history, never ranked against another.

Cost vs Rework

By team · Last 90 days

Each team is measured against its own history — never ranked against another team.

Paying offCostly / frictionOn budgetBurning

For the CFO

A budget decision, not another dashboard.

Each team’s AI spend against the budget you set, with a call you can act on: raise, hold, or review. Defend every AI dollar with what the work actually shows.

AI budget

This month

AI spend versus budget by team, the return on each team's next dollar of AI spend, and a recommended call for each.
Team	AI spend/mo	Budget	vs budget	Marginal return / $	Call
Platform (Engineering)	$92K	$85K	+8% over	$1.82	Raise
Payments (Engineering)	$118K	$95K	+24% over	$0.34	Review
Tier 1 (Support)	$64K	$65K	on budget	$1.08	Hold
Mid-market (Sales)	$71K	$60K	+18% over	$0.52	Review

Apply all → $31K/mo shifts toward teams where AI pays off.

How it works

Low lift, fast payoff. Setup is a conversation, not a rollout project — you’re seeing your return in weeks.

Which areas do you want to onboard?

EngineeringSupportSales

GitHubEngineeringConnected · read-only

01 Connect — in an afternoon.

Tell an agent which areas to onboard, drop in your org chart — a screenshot works — and connect your tools, read-only. A conversation, not a rollout project.

02 Measure — against your own history, in weeks.

We measure what each team produces, the rework it took, and what the AI cost — each team compared only to its own baseline, never ranked against another team.

Give support AI examples of your best resolved tickets

Impact: HighEffort: Low

Name an owner for your AI setup

03 Act — on a decision, not a dashboard.

See where AI pays off, where it burns, and the exact next fix — then watch the trend confirm it worked.

Everyone measures the inputs. AIReturn measures whether it worked.

Everyone measures the inputs. AIReturn measures whether it worked.
	AI cost	Model quality	Compliance	Did the work get better?
AI cost / FinOps tools	AI cost / FinOps tools: AI cost — yes	AI cost / FinOps tools: Model quality — no	AI cost / FinOps tools: Compliance — no	AI cost / FinOps tools: Did the work get better? — no
AI observability / monitoring	AI observability / monitoring: AI cost — no	AI observability / monitoring: Model quality — yes	AI observability / monitoring: Compliance — no	AI observability / monitoring: Did the work get better? — no
AI governance tools	AI governance tools: AI cost — no	AI governance tools: Model quality — no	AI governance tools: Compliance — yes	AI governance tools: Did the work get better? — no
AIReturn	AIReturn: AI cost — yes	AIReturn: Model quality — no	AIReturn: Compliance — no	AIReturn: Did the work get better? — yes

AI cost / FinOps tools

AI cost
Model quality
Compliance
Did the work get better?

AI observability / monitoring

AI cost
Model quality
Compliance
Did the work get better?

AI governance tools

AI cost
Model quality
Compliance
Did the work get better?

AIReturn

AI cost
Model quality
Compliance
Did the work get better?

…and the only one that measures it across every team — not just engineering.

Connects to your stack

Reads the work where it happens.

Code, tickets, deals, product — AIReturn connects to the tools your teams already use. Read-only.

OpenAI

Anthropic

GitHub

Linear

Jira

Salesforce

HubSpot

Zendesk

Intercom

GitLab

Gong

Pipedrive

Cursor

GitHub Copilot

Bitbucket

Azure DevOps

Shortcut

Productboard

Airtable

Freshdesk

Front

Help Scout

Gorgias

Kustomer

Freshservice

ServiceNow

Zoho CRM

Outreach

Salesloft

MS Dynamics

Read-onlySee all integrations

What changes for you

Defend your AI budget to the board with a real number.

Cut the rework quietly burning your AI spend.

Double down on the teams where AI actually pays off.

Priced to your results, not your headcount.

Pricing depends on your AI spend — you pay a small fraction of what you put under management, so our price only grows when your AI investment does. No per-seat games.

Stop guessing whether your AI is worth it.

Get a clear return-on-AI picture in weeks.