We Place Users at the Center of Search


Predictive search results using Auto Suggest mechanism through suggesting search terms and recommending results in the search bar.


Relevant search results rooted in document quality using Pairwise and Listwise ranking.

Personalized Search Results

Personalized search results using AutoML for known users and Markov Chain attribution model for anonymous users.

How does it work?

Import Data

SearchBoost.ai imports your user behavior from your data source like Adobe Analytics, Google Analytics, etc.

Step 1

Import and Train Search Results

Import search results from your search tool then train it using our proprietary machine learning models

Step 2

Push to Search Engine

After the new smart results are produced, SearchBoost.ai pushes those results to your search engine like Apache Solr, Elastic, etc.

Step 3

Serve Customers

Once your search engine has the new results, they would serve your users on your site with them

Step 4

Gather Insights

Also you will have a number of reports and dashboards showing you insights on the performance of SearchBoost.ai, including in your data analytics and in our own dashboard using Power Bi

Step 5

Rinse and Repeat

After the first deployment with SearchBoost.ai, you can run and iterate a new training batch over time to continue to improve and optimize your search results based on what your users do.

Step 6