Neurolinx Documentation

How it Works

At Neurolinx, we leverage advanced artificial intelligence and machine learning algorithms to deliver personalized recommendations and search results across various industries. Our technology works by analyzing vast amounts of data, including user interactions, reviews, and product descriptions.

Source Data

We source our data from trusted suppliers and categorize it into three main categories:

Our data is categorized into three main types:

We prioritize data privacy and security. Your information is kept private and secure, accessible only to authorized personnel within our company. Your data will not be used for any other purpose without your prior consent.

Engineering Process

The essence of our engineering process lies in keeping things simple for you. Neurolinx's prompt engineering process utilizes advanced automation to reduce the time and resources needed to build a powerful and effective recommendation engine tailored to your business needs.

The Simple Steps Needed

We have pre-collected data from three industries: Beauty & Cosmetics, Movies & TV, and Travel. If your business is included in any of these three categories, the process should take approximately one month. If your business falls outside of these industries, the entire process should take around three months to complete.

• Transmit Your Item Library: Share information about your business goals and item library data with us. You can transmit the data through your preferred channel (we're flexible). Past methods of communication used by our clients include cloud storage software, messenger services, and email.
• Data Preprocessing: We will begin by mapping your item data with user language data. If your site includes real user reviews of items, please provide us with your review data to enhance the relevance of your Data Science and Customer Management (DSCM) system. Rest assured, the review data you share will only be used to improve the relevancy of your DSCM system and will not be shared with any other parties or used for other projects.
• Model Training: We will initiate the basic training and customization of the Neurolinx ML model. During this stage, we will conduct A/B tests of various algorithms and filtering techniques to identify the most suitable ones for your business objectives. Once we have determined the optimal methods, we will calculate and refine the semantics to be used as new search and recommendation signals. The duration of this step will vary depending on factors such as the size of your item library and your desired business goals.
• Transfer Results: Once the Neurolinx model is deployed, we will transmit the results using an API.
• Check Results: If you encounter any counterintuitive or seemingly implausible results while reviewing your received data, don't worry. This can happen because AI understands everything through numbers and scores, while humans achieve understanding on a more collective basis. To address this, you can access our Solution Admin page to make any necessary adjustments to the AI-generated results. Click here to learn more about the functions and uses of our Solution Admin.

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