For PE-backed and mid-market teams under pressure to prove AI ROI

AI transformation that shows up in EBITDA, not another science project

Metacto finds the one workflow worth funding, builds the agentic system around it, and proves the impact on revenue, margin, speed, quality, or risk.

Get the AI ROI Assessment

See where AI can move a real business number. No technical prep required.

20+ years building production software. 100+ products shipped.

Trusted by operators at PE-backed and mid-market companies

5.0 on Clutch
The AI ROI gap

AI adoption is everywhere. AI ROI is not.

Almost everyone has AI tools. Far fewer can name the business metric that moved. ROI takes workflow change, and workflow change takes an owner.

88%
use AI in at least one business function — near-universal adoption
20%
capture 74% of AI’s economic value — value is concentrated
5%
see measurable P&L impact — almost no bottom-line return

Sources: McKinsey, The State of AI 2026 · PwC, 2026 AI Performance Study · MIT Project NANDA, GenAI Divide 2025

See where you land
AI maturity

AI activity is not AI maturity.

Claude, Copilot, GPTs, and dashboards aren't maturity. The question isn't who uses AI. It's where AI has changed how work gets done.

Most teams stall at activity. Metacto moves you to measured impact.

The maturity questions that matter:

  • Which workflow should change first?
  • Who owns the business metric?
  • What is the baseline today?
  • How do we avoid a science project?
Where AI moves EBITDA

Where AI ROI actually shows up.

Revenue

Sharper qualification, faster follow-up, better conversion.

Margin & cost

Less manual review, fewer repeats, lower cost per output.

Speed

Shorter cycle times, faster approvals and reporting.

Quality

More consistent decisions, fewer errors and rework.

Risk & compliance

Earlier exception detection, clearer audit trails.

Find where AI can move EBITDA
Baseline

Pick the number that proves it was worth it.

Every workflow has a leading metric that moves early and rolls up to one of the five values the business runs on: revenue, margin, speed, quality, risk.

A leading metric that moves now, tagged with the value it ladders up to.

Revenue
Win rate 18% → 23% +5 pts
Margin
Cost per output $48 → $26 −46%
Speed
Cycle time 31d → 12d −61%
Quality
Rework rate 9% → 3% −67%
Risk
Missed exceptions 6 → 1 −83%

Illustrative. Every engagement measures the real baseline first.

We define, before any build:

  • The leading metric, and the value it rolls up to
  • The baseline today, and what the gap costs
  • The build / no-build threshold
The baseline is the business case.
Map your baseline
Demo vs. business case

The demo is not the business case.

A great demo is the easy 5%. Metacto builds the other 95% that makes AI pay back in production.

The demo 5% Model capability, a chat interface, a prototype workflow, demo data. The part you've already seen.

The Production System · 95%

  • Business context So the system understands how your business actually works.
  • Source-of-truth data So answers are grounded in real records, not guesses.
  • Role-based access So people only see and do what they should.
  • Rules & exceptions So the system respects policy and the edge cases.
  • Approval paths So the right actions wait for a human.
  • Human review So judgment stays with your team.
  • Write-backs So results land in the systems work already runs on.
  • Logs & audit trails So leaders can see what happened and why.
  • Monitoring & cost So errors, latency, usage, and spend stay visible.
  • Adoption & ownership So the workflow is used, and owned, after launch.
  • ROI measurement So business impact is tracked, not assumed.
Pressure-test your AI business case
Proof

What this looks like in production.

Education · Scholarship access

A manual scholarship operation, rebuilt as a platform, then agents that find and structure opportunities.

Metacto replaced spreadsheets and manual research with a purpose-built platform, then layered an agentic workflow that searches, enriches, qualifies, and creates scholarship records, with admins in the loop.

Enterprise impact  ·  Revenue · Quality · Speed

“My results weren't diluted with technology. Being tech-enabled lets me see what's going on, and that transparency builds trust.”

Founder, Securing Degrees
$7.8M

in verified private scholarship wins, across fewer than 400 active students

  • 3,000 applications started on the platform
  • 60%+ of started applications reach submission
  • 80%+ of edited essays convert to wins
More in production
Marketing agency

Lead & deal agents for RevOps

$1.4M added pipeline

17% → 22% win rate

Revenue · Speed

Construction payroll

Embedded compliance copilot

$320K annual capacity recovered

1.67× analyst output

Risk · Margin

Request the case studies
Process

From scattered AI to one funded workflow.

Start with a number worth changing. Then build the system to change it.

01 · Find the value

Opportunity Map

You get Ranked opportunities and a recommended first workflow.

02 · Build the context

Context Layer

You get Data, rules, access, and a measurement plan.

03 · Ship AI

Agentic workflow

You get A live workflow with human review and integrations.

04 · Measure & expand

Continuous AI Ops

You get ROI reporting and an expansion roadmap.

Decision packet

Built so the whole team can say yes.

Sponsor, operator, and IT each get what they need to decide.

Sponsor

For the sponsor

What to fund, the expected ROI, and who owns the metric.

Operator

For the operator

What changes, what stays human, and where exceptions go.

IT & security

For IT & security

Systems touched, data used, and the controls required.

One assessment, one decision the whole team can get behind.
Fit

Is this right for your team?

A fit when
  • You have real pressure to prove AI ROI, not just increase AI usage.
  • A workflow's manual work, review time, coordination, or missed decisions are affecting revenue, margin, speed, quality, or risk.
  • Someone on the leadership team owns the outcome and can change how the work gets done.
  • You want a clear first investment before scaling AI across the business.
Probably not a fit if
  • You mainly want training, prompts, or a lightweight AI workshop.
  • You want to test AI without changing a real workflow.
  • The business problem is still too vague to measure.
  • There is no owner for the outcome after launch.

Questions before you start.

How is this different from an AI pilot?

Pilots prove something is possible. We start from business value, pick one workflow, baseline it, and give a build / no-build call, so you fund a measurable investment instead of another demo.

What do we get from the assessment?

An AI maturity snapshot, a ranked AI Opportunity Map, a baseline and ROI hypothesis, a first-workflow recommendation, and build / no-build guidance.

How do you quantify AI ROI?

We baseline the workflow and define the leading metrics before any build, then track them against that baseline after launch, so impact is measured, not assumed.

Do we need a mature data stack first?

Not always. Part of the assessment is identifying exactly what data, context, rules, and access a workflow needs before building, and what can wait.

Can you work with our IT and security teams?

Yes. Access controls, permissions, documentation, and auditability are part of the work, so it is easy to bring IT and security in early.

What happens after the assessment?

You get a build / no-build recommendation and a phase-one roadmap. If the business case is strong, Metacto can build the agentic workflow and measurement layer.

AI ROI Assessment

Find the first AI investment worth funding.

Before you fund another pilot, get the workflow worth building first, its baseline, and a build / no-build call.

You leave with:

  • An AI maturity snapshot
  • A ranked AI Opportunity Map
  • A baseline and ROI hypothesis
  • A first-workflow recommendation
  • A build / no-build call

Clarity before another pilot.

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