Independent AI Verification
Did it run? Did it work? Whose fault?

Your AI closed the ticket. Did it solve the problem?

Monitoring proves your AI ran. It can't prove it worked. We can — independently. MarginSignal OS measures whether your AI actually lowered the cost of reaching the right answer, and when it doesn't, names whose fault it was: data, model, operator, or agent. Evidence that holds up, because it doesn't come from the people being graded.

Commercial and findings terms are governed by written agreement; sample outputs are illustrative until validated against client data.
Book a Findings Call See a sample verdict →
Built For: Insurance Claims Ops Healthcare & RCM BPO / MSP

What We Actually Do

Independence Is a Requirement

An operator grading its own AI is the conflict. We're the outside check — the same independence principle finance and safety already run on: EU AI Act Article 31 for conformity bodies, SEC/PCAOB auditor rules, the lesson of the 2008 credit ratings. The party with a stake in the answer can't be the one who certifies it.

Outcome, Not Activity

A dashboard counts the first contact. We follow the whole journey to the real resolution and put an honest dollar cost on it — your true Cost Per Resolution. Did the AI make the right answer cheaper, or just the call faster?

Fault Attribution for Agentic AI

When a chain of agents drops the ball, "the AI failed" isn't an answer. We pinpoint where it broke — data, model, operator, or the exact handoff — in evidence a skeptic can reproduce.

Why the evidence holds up

The MarginSignal engine

The defensibility isn't a brand or a patent — it's the structure of how the evidence is produced: independent, externally anchored, and reproducible by someone who doesn't trust the operator. (Core methods patent-pending.)

Externally anchored
Evidence you don't have to trust the operator to believe.
Independently reproducible
A skeptic can recompute the same result.
Cross-party attribution
Fault apportioned across data, vendor, operator, and agent.
Structurally neutral
An operator, vendor, or insurer can't produce it — you can't grade your own homework.
Independent AI Verification · Sample Readout

What an independent verdict looks like

One AI-handled resolution, measured from outside the operator. Illustrative sample.

Did the AI work?
Not resolved
A contact like this would close as ‘resolved’ — then the customer comes back 9 days later.
True cost to resolve
$214
reported: $38
Fault attribution
Data
✓
Model
✗
Operator
✓
Agent handoff
✗

On a failure like this, fault would land on the model-vendor — correct inputs, wrong determination, dropped at the agent-3 handoff.

Independently reproducible — verifiable by a party that does not trust the operator. Illustrative sample.
Grounded In Established Practice

Our methodology builds on established service-economics frameworks and published research — the COPC CX Standard, ICMI and HDI practices, and research from Deloitte and McKinsey. We didn't invent these concepts; we built the system that computes them reproducibly and independently.

References to third-party standards and research do not imply endorsement, affiliation, or sponsorship.

As Featured On BUSINESS RADIOX Atlanta Business Radio
with Lee Kantor
16
Structural Fault Lines Mapped
$35+
Avg CPR Gap Per Resolution
Scoped
Findings Terms by Written Agreement
Zero
Baseline Period Required

Why can't my data team build this in-house?

Resolution-chain reconstruction is not a default BI model. It requires tracing every contact from first touch to final closure across systems.

CPR economics requires operational domain logic, not just dashboarding. SQL alone doesn't assign dollar impact to behavioral fault lines.

Fault-line mapping takes 15 years of operational pattern recognition, not a sprint with your analytics team.

Time-to-value is weeks, not quarters. Internal build cycles take 3-6 months to scope, build, validate, and get executive buy-in.

What the system actually produces

See Sample Output

MarginSignal OS turns operational telemetry into an executive view of margin health, drift signals, proof windows, and fix accountability.

Operations without MarginSignal OS: Margin Health Score 48.6, -$9,500 margin lost, CPR rising $4.32 per resolution, critical alerts across all metrics Operations with MarginSignal OS: Margin Health Score 74.2, $94,500 protected margin, CPR improving, all systems healthy

Same operation. Same baseline. The difference is whether structural leakage gets diagnosed and contained — or compounds for 90 days.

Illustrative sample environment.

90-Day Proof Scorecard showing 2 of 6 fixes complete with fix accountability across decision rights, workflow design, instrumentation, and behavioral categories

Illustrative sample environment. 90-day proof scorecard.

Monthly Cost-Per-Resolution Drift chart showing $94,500 protected margin over 30 days with -$1.84 per resolution drift

Illustrative sample environment. CPR drift view.

Predictive Forecasts showing 3-month projections for Transfer Depth, Cost Per Touch, Cost Per Resolution, and Margin Health with threshold breach warnings

Illustrative sample environment. Predictive forecasts.

Try the Preliminary Scanner yourself, review the full sample output, or book a guided live demo of the MSOS Terminal. The live Terminal itself is invite-only with authenticated tenant access.

See full sample deliverable set Become a Design Partner

The Problem Nobody Is Measuring

Your dashboards prove activity, not outcomes. The cost bleeds inside repeat contacts, transfer chains, escalation loops, and AI handoffs that close the ticket without solving the problem — and it rarely surfaces in standard reporting. Automation doesn't fix the leak. It runs it faster.

These friction patterns compound silently — a 3% repeat rate is not 3% waste. It is 3% compounding across every resolution chain, every day, in every domain you operate.

The Signal Gap

Why Dashboards Miss Structural Leakage

What The Dashboard Shows
Average handle time: 7.2 minutes (Stable)
What It Doesn't Say (Floor Reality)

↳ 22% of interactions required a callback within 7 days.

↳ The callbacks averaged 12 minutes.

↳ 3 of them escalated (Authority Misalignment).

↳ 1 dispatched a truck.

That "7-minute interaction" actually cost you 47 minutes of operational capacity and a $180 truck roll.

The Diagnostic Framework

We map 16 structural fault lines — including AI handoff degradation — to our CPR (Cost Per Resolution) economics model. Built from your operating data, not generic industry averages, and reproducible by someone who doesn't work for you.

Baseline-Free Delivery From Day 1
MSOS Diagnostic Output // 12-Card Set
The Pivot Point Structural Fault Line Predictive Driver Financial Impact
Transfer Count > 2 Ownership Diffusion Across Handoffs Transfer Depth AWAITING...
Escalation Returned Escalation Bounce (Authority Misalignment) Escalation Bounce Rate AWAITING...
Revisit within 14 Days Field Revisit Normalization 7-Day Repeat Rate AWAITING...
01 // DIAGNOSE

16 Fault Line Cards

We map your telemetry against 16 structural fault lines, including AI handoff degradation where supporting data exists. No 8-week baselining period required.

02 // QUANTIFY

CPR Economics

Every repeat contact, transfer chain, and escalation loop has a dollar value. We calculate the true Cost Per Resolution — not per call, per resolution — so you see what it actually costs to make a customer issue go away.

03 // CONTAIN

Behavioral Playbooks

Every Fault Line is assigned a "Moves-First Metric." We deploy behavioral coaching kits and 30-day containment plans giving leaders exact architectural corrections.

Design Partner Program

Be the first reproducible AI verdict.

We're selecting a small number of design partners to produce the first public, reproducible CPR verdicts — on defined terms, at no or reduced fee. Going first should be easier than not.

No client logos to show you yet. That's the point: no other operator to protect, no result we've had reason to soften.

See the terms & apply
Preliminary Scanner

Run a Preliminary Diagnostic.

Describe a friction pattern wherever AI is handling resolutions. The Scanner maps it to one of 16 structural fault lines and surfaces a preliminary exposure range. Book a Findings Call to confirm against your data.

Prefer numbers? Try the 30-second CPR Gap Calculator →

Use generalized examples only. Do not enter client names, PHI, PII, ticket IDs, or confidential operational data.

Or try a common signal:
MSOS // Cognitive_Gate_0

Awaiting Telemetry

How MarginSignal Is Delivered

Not software-only. Not consulting-only. An independent measurement system — from first assessment to continuous, verifiable proof.

Step 1

Entry Point

Start with an Exposure Review. We confirm fit, data readiness, and the most likely fault-line hypothesis before recommending a diagnostic scope.

Exposure Review Preliminary Hypothesis
Step 2

Diagnostic Engagement

A scoped verification or a full diagnostic. We ingest your data, reconstruct resolution chains, and deliver ranked fault lines with dollar impact.

Scoped read Full diagnostic
Step 3

Platform Layer

Dashboard access, drift monitoring, alerting, audit trail, and ongoing executive review. Continuous visibility into margin health — not a one-time PDF.

Dashboard Drift Alerts Audit Trail
Auto-Detected Platforms
Connect
Wise
Auto
task
Service
Now
Fresh
desk
Custom
CSV

We auto-detect ticket structure from the platforms your operation already runs on. No API integration required.

Don't see yours? Custom CSV intake supported.

Frequently Asked Questions

Do you need direct integration with our CRM/Telephony databases?
No API integration is required for the initial diagnostic. We can run the CPR economics model using approved, anonymized operational exports, then scope any API, SSO, or security-review requirements separately for enterprise deployments.
How much time will this require from my management team?
Minimal. Our entire philosophy is that "Data Insufficient is a feature, not a bug." We do the heavy analytical lifting. Your team only needs to provide the raw exports and attend a 60-minute Executive Briefing where we present the containment strategy.
We already have a BI team. Why do we need MSOS?
BI teams are excellent at building dashboards that show you averages. However, BI teams are rarely operational practitioners. MarginSignal OS doesn't just display data; we map the data to 16 specific fault-line patterns and translate those structural failures into a CFO-ready financial exposure model.
Brandon Burdin, Founder of MarginSignal OS
Atlanta, GA

Brandon Burdin

Founder

  • 15 years in customer-experience and operations analytics
  • Former telecom analyst — outlier-KPI and churn modeling
  • Measurement across insurance, healthcare, BPO, and field service
  • Caregiver to his father, a disabled veteran

I spent 15 years measuring whether service operations actually worked — and watched “resolved” tickets quietly reopen while the dashboards stayed green. MarginSignal OS answers the only question that matters now that AI is doing the resolving: did it actually work, and at what true cost?

The why is personal. My father is a disabled veteran I care for, and navigating his claims taught me what happens when no one independent is checking whether the system delivered. I'm one person, on purpose — no operator to protect, no result I've had reason to soften. That's what an independent verifier is supposed to be.

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Request a Diagnostic

Every engagement is led directly by the founder and scoped for hands-on execution.

Request Received.

I'll review your details and reach out within 24 hours to schedule a brief scoping call.

Your Dashboard Says Green.
Your Margin Says Otherwise.

The gap between Cost Per Call and Cost Per Resolution is structural. It compounds daily. And it is invisible to every dashboard in your building. We find it.

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