Knowledge Management

Allowing employees to share, find, access and update business knowledge is key to allowing companies to run productively and make decisions more effectively and efficiently. Most companies manage this manually. AI can enhance both employees' ability to find the knowledge they are looking for and suggest knowledge that seems relevant to them.


Improve search results and suggest relevant documents to allow for better sharing of business knowledge.


Relevant pages to a user.


The primary problem is to create a record for every employee that captures which types of documents that the employee has used in the past. This is similar in scope to building the data for a recommendation engine for an ecommerce company. Further, all the documents will need to be processed by text analytics tools to extract relevant characteristics for the recommendation engine and to support natural language search. All this data needs to be cleaned, joined and transformed into valuable ML features before going into model training. This pre-modeling prep process can be frustrating and time consuming. We are here to help.

Modeling techniques and libraries

Extract text features

Using a natural language processing toolkit, extract the relevant features from the file.

  • NLTK
  • CoreNLP
  • Gensim
  • spaCy
  • Polyglot
  • Pattern

Content-based filtering

Use the attributes of the products a customer has used/purchased to find other products that have similar attributes.

  • Sklearn


Build a high-quality search engine to enable quick searches of the documents.

  • Scout
  • Whoosh

Related accelerators

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No-code/low-code data prep and visualization