NEW! SearchBlox is now an Adobe Platinum Technology Partner. I Get Started.

NEW! SearchBlox is now an Adobe Platinum Technology Partner. I Get Started.

NEW! SearchBlox is now an Adobe Platinum Technology Partner. I Get Started.

Private AI Personalization white paper hero background

Private AI Personalization

Private AI Personalization

Delivering 1:1 Experiences Without Sending Customer Data to the Cloud

Delivering 1:1 Experiences Without Sending Customer Data to the Cloud

Download the White Paper

Free download | 13-minute read

For years, enterprises have been told that better personalization requires more customer data, larger profiles, and more behavioral signals sent into cloud-based AI platforms.

For years, enterprises have been told that better personalization requires more customer data, larger profiles, and more behavioral signals sent into cloud-based AI platforms.

That model is getting harder to sustain.

Customers expect relevant, individualized experiences. They also expect their personal information to be protected. And enterprises are under growing pressure to control where data is processed, how long it is retained, and which AI models can access it.

That raises a strategic question:

How do you deliver a truly 1:1 AI experience without turning customer data into an external AI dependency?

How do you deliver a truly 1:1 AI experience without turning customer data into an external AI dependency?

Our new white paper answers it.

Preview of the Private AI Personalization white paper by SearchBlox

Download your free copy
of the White Paper

Download your free copy
of the White Paper

The next phase of personalization is not just smarter. It is private.

The next phase of personalization is not just smarter. It is private.

Private AI Personalization white paper cover

Get your free copy

13-minute read

Inside the paper

Inside the paper

Why real-time intent beats static customer profiles

Why real-time intent beats static customer profiles

The five layers of a private personalization architecture

The five layers of a private personalization architecture

How private inference removes per-token costs

How private inference removes per-token costs

Five ways to limit data exposure

Five ways to limit data exposure

Six questions to answer before you implement

Six questions to answer before you implement

Private AI Personalization white paper cover

Get your free copy

13-minute read

Personalization Has Become a
Data Governance Problem

Personalization Has Become a
Data Governance Problem

Personalization runs on context - search queries, clicks, products compared, purchase history, account information, and current session intent.

The more signals an AI system understands, the more relevant the experience becomes.

But those same signals are sensitive. Every time customer context is sent to an external AI provider, it raises questions about data residency, access, retention, and third-party processing.

For enterprises in regulated or data-sensitive industries, privacy can’t be an afterthought to personalization.

It has to be part of the architecture.

Search queries

Clicks

Products compared

Purchase history

Account information

Current session intent

What You’ll Learn in the White Paper

What You’ll Learn in the White Paper

01

Why customer profiles aren’t enough, and how real-time intent changes what personalization can do

Why customer profiles aren’t enough, and how real-time intent changes what personalization can do

02

How RAG grounds personalization in current product, pricing, and policy information

How RAG grounds personalization in current product, pricing, and policy information

03

The five layers of a private personalization architecture - from customer context to private AI reasoning

The five layers of a private personalization architecture - from customer context to private AI reasoning

04

The difference between recommendations and intelligent personalization, and what moves an experience closer to 1:1 guidance

04

The difference between recommendations and intelligent personalization, and what moves an experience closer to 1:1 guidance

04

The difference between recommendations and intelligent personalization, and what moves an experience closer to 1:1 guidance

05

How private inference changes AI economics, shifting costs away from per-token pricing for high-volume workloads

How private inference changes AI economics, shifting costs away from per-token pricing for high-volume workloads

06

Five ways to limit data exposure without limiting personalization

Five ways to limit data exposure without limiting personalization

07

Six questions to answer before implementing private AI personalization

Six questions to answer before implementing private AI personalization

Get the full picture

Personalize every experience. Keep your data private.

See how enterprises combine real-time intent, RAG, and private LLMs to deliver 1:1 experiences inside their own security boundary - then book a demo to see it running on your data.

Get the full picture

Personalize every experience. Keep your data private.

See how enterprises combine real-time intent, RAG, and private LLMs to deliver 1:1 experiences inside their own security boundary - then book a demo to see it running on your data.

Enterprise team reviewing private AI personalization results

Get the full picture

Personalize every experience. Keep your data private.

See how enterprises combine real-time intent, RAG, and private LLMs to deliver 1:1 experiences inside their own security boundary - then book a demo to see it running on your data.

Enterprise team reviewing private AI personalization results
SB-Logo