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:
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Social Data: This encompasses online reviews, blogs, Twitter,
and other social media platforms.
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Internal Data: This category includes first-party data like
engagement metrics, additional text data, and other user
interaction data.
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Second-Party and Third-Party Data: This consists of images,
detailed item attributes, distribution channels, price
information, and more.
Our data is categorized into three main types:
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Item Metadata: This category includes unique ID values for
each item, item names, review data, and other relevant
information.
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User Events/Interactions: This category encompasses user
engagement data, such as likes, clicks, and view metrics.
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Second-Party and Third-Party Data: This consists of images,
detailed item attributes, distribution channels, price
information, and more.
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.
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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.
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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.
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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.
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Transfer Results:
Once the Neurolinx model is deployed, we will transmit the
results using an API.
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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.
Introduction
