Your Media Auditor Should Live Where Your Data Lives
The Auditor Goes to the Evidence
CleanTap runs beside approved datasets inside your controlled environment. Audit logic comes into the data boundary, and only controlled findings come out.
Your controlled environment
Media logs
S3, GCS, or warehouse
Billing data
finance and supplier exports
Taxonomies
device and vendor reference maps
Terms and plans
contracts and benchmarks
Scoped read access
approved sources and fields only
CleanTap Auditor
Local execution
Controlled output layer
reason-coded aggregates and case files
Findings
bounded, reproducible populations
Evidence packets
traceable vendor case files
Reconciliation
billing and definition questions
Controls
versioned monthly QA rules
Raw logs stay put. The audit comes to your data, and only controlled findings cross the boundary.
Three Views of Every Media Event
The agents ask one question of each event: do the device, the content, and the connection tell a coherent story?
Device
Is the device real and correctly declared? The auditor resolves hardware and form factor instead of trusting a strategy label.
Content
Is the environment what it claims to be? Publisher, app, bundle, and channel signals are mapped and checked against each other.
Connection
Does the network path make sense? Household traffic is separated from data-center and server-mediated delivery.
A Repeatable Audit Pipeline
The population is defined before anything is judged. Proven findings stay separate from claims that depend on another party.
01 / Assess
What is actually here?
Chain of custody and schema integrity, then a defensible analytical population.
02 / Inspect
Where did it run?
Device, content, and connection context for every event, plus geography and app transparency.
03 / Investigate
How did it behave?
Supply path, timing, clustering, server origin, and duplicate patterns.
04 / Bound
What can we prove?
Verified findings, review cohorts, reason codes, and explicit dependencies.
05 / Deploy
What changes now?
Billing reconciliation, vendor case files, recurring controls, and future filtering.
An Anomaly Is Not a Verdict
Every finding carries a status, so vendor conversations start from evidence instead of suspicion.
Verified observation
Reproducible from supplied data.
The rule and its result can be rerun directly against approved records, denominator included.
Example: repeated impression-ID review population
Interpretation to confirm
A supported explanation that still needs confirmation.
Correlated signals point to a plausible mechanism, but the log fields alone cannot establish it.
Example: server-origin pattern consistent with intermediary delivery
External dependency
The missing file is part of the finding.
Some conclusions wait on official field definitions, billable counts, rates, or contract terms.
Example: "was this population billed?"
The goal is questions that survive the vendor meeting.
546,828,755 Rows, One Auditable Story
A recent enterprise CTV review began with the full delivered extract: 1,667 S3 objects holding 546.8 million rows. The population narrowed only after the chain of custody was established.
A strategy label is not an observed device, and an observed device is not a billed impression.
The audit keeps those layers separate until the evidence reconciles them.
Sometimes 136 Rows Matter More Than 136 Million
A tiny cohort can expose a category contradiction that aggregate dashboards never surface, and explain how the door stayed open.
One Audit Layer, Different Leverage
Hard-won audit logic becomes versioned controls that run every month, on both sides of the client relationship.
For Brands
Own the independent record of what happened.
- Inspect delivery outside vendor dashboards
- Reconcile supplier and billing views of the same campaign
- Keep audit logic and definitions when partners change
- Escalate only the cohorts worth a meeting
For Agencies
Give clients forensic depth without building a lab.
- Standardize media QA across accounts
- Keep client logs in client-controlled environments
- Deliver consistent vendor escalation packets
- Make independent evidence part of the service
Least Movement of Data
Deployments adapt to your cloud and governance standards. The core principle is to minimize what crosses the boundary.
Scoped access
Only approved sources and fields are exposed to the auditor.
Read-oriented design
Source tables remain authoritative. Output is written to a separate evidence layer.
Reason-coded findings
Every escalated cohort carries the rule and denominator that created it.
Traceable lineage
Aggregate claims tie back to controlled event-level evidence.
Agentic Orchestration, Deterministic Evidence
The agent chooses the next analytical step. The evidence still resolves to a reproducible rule and population, with an explicit status and dependency.
RULE CTV_DEVICE + NON_VIDEO_CREATIVE POPULATION 4,635,814 EVENTS STATUS CREATIVE RENDER REVIEW DEPENDENCY SUPPLIER DEFINITION REQUIRED
Keep the Logs. Add the Audit Layer.
We scope each deployment around your data location, available event-level fields, channels, and governance requirements.