Deep scrutiny on every ad, without the personal data.
TechnologyWe evaluate three signal domains on every bid-request, chosen because they are scalable, reliable, and durable, and because they do not depend on sensitive personal information.
This is the engine behind our point-of-entry filters and the flagship agentic always-on audits.
The signal model: device, content, connection
On every ad we check three things. For buyers, this is why the supply you pay for is real: the device, the content, and the connection are all vetted before money moves.
Device
Is the device real, eligible, and correctly declared? We resolve device objects against the long tail of spoofed and misdeclared hardware.
Content
Is the content and channel what it claims to be? We validate publisher and content declarations against observed behavior.
Connection
Is the network path legitimate? We separate residential from data-center and proxy traffic at the ISP and telco layer.
Every check runs without sensitive PII, so quality holds up even as identity signals disappear. Privacy-durable by design: no reliance on identity graphs or sensitive personal data.
The engine: filter & enrichment, at the point of entry
With those checks in hand, we reject unsuitable supply at the point of entry and enrich the rest, so buyers only pay for eligible requests.
Seller
SSP / Network sends bid-requests.
CleanTap
An immediate device-object filter rejects unsuitable supply, each with a transparent no-bid reason. Suitable supply is enriched for curation.
Buyer
DSP / ATD receives clean, enriched, eligible requests.
Enriched, eligible bid-requests are routed to buyer endpoints; responses are relayed and win/loss is reconciled, all while applying deep scrutiny to every single request.
Filtering is only half of the engine. We also audit the flow after the fact, over your own logs, to prove where quality and money leaked.
See how agentic auditing worksUnder the hood
An unusually advanced infrastructure stack, run by unusually serious people.
Screening tens of billions of requests a month, and running always-on audits inside customers' own environments, only works because of how we combine three things most teams treat separately.
Cloud storage
Architected so audits and filtering run where the data already lives, so customers never have to ship sensitive logs out to be inspected.
Local compute
Mostly-local compute keeps deep, log-level scrutiny fast and cost-efficient at enormous volume, the opposite of pay-to-look.
Multi-model workflows
Agentic pipelines orchestrate several frontier models alongside local tooling, so auditing agents run always-on, customized, and reproducible.
This stack is built and run by the same specialists behind our work, in Web Infrastructure, Consumer Psychology, and Media Advertising. AI is the method we thread through all of it, not a substitute for that expertise. That combination is rare, and it's the reason CleanTap can do at the point of entry what most of the market still can't do at all. Meet the team →
Bring the framework to your data.
Deploy an always-on auditing agent inside your own infrastructure. You keep the data, we bring the expertise.
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