It reads the context of each session in real time (referral, channel, device, in-session behaviour) and enables a response matched to the moment, before the page renders. The result is more revenue per session, less unnecessary discounting, and richer first-party signal.

No. A CDP organizes customer data and identity. Personalization decides what to deliver from the signals it has. CRO optimizes the page for conversion. InferKNOW sits upstream of all three: it reads the live session, including when there is little or no identity, and gives downstream systems a signal they couldn't generate themselves.

Session Yield Management: higher revenue per session and less margin leakage from existing traffic, without replacing your commerce, marketing or analytics tools. Contextual first-party data is an added benefit.

A Context Layer between existing Identity and Marketing/Personalization infrastructure. Downstream systems learn what is happening in the current session, which historical identity data alone can't tell them.

No. No identity is required. InferKNOW reads signals from the live session, so it works on visitors identity systems can't resolve, including AI-referred visitors and autonomous agents.

It doesn't depend on storing a permanent personal profile. It interprets the current situation and responds in real time.

It detects agent traffic and offers structured, negotiable terms: machine-readable pricing, bundles and conditions the agent can act on directly. That also lowers agent latency and token cost compared with parsing a human-oriented page.

A single script and roughly four hours of engineering. The layer is live in about 48 hours, with no re-platforming.

Against a holdout group. The +200% purchase completion and +57% yield-per-session gains come from comparing visitors who receive the InferKNOW response with visitors who don't.

Not entirely. InferKNOW infers context from live session signals rather than stored personal data, so it can operate in many cases without explicit consent. Where consent has not been given, the signals available to the inference layer are narrower and the contextual read is correspondingly less precise. It still works. It is simply working with less.

No. InferKNOW does not depend on cookies or tracking pixels. It was designed for an environment where those mechanisms are unavailable or restricted — reading only the signals present in the live session: referral, channel, device characteristics, and in-session behaviour. First-party data, where it exists, enriches the inference. It is never a requirement.