44% of knowledge management experts believe that AI can be used to provide
highly relevant information or articles.
With the explosion of digital information, organizations need to find new and effective ways to
manage, process, and analyze the massive amounts of data at their disposal. This is where
Knowbler comes in.
By leveraging the power of artificial intelligence (AI), Knowbler helps organizations automate the
process of knowledge creation and maintenance. Apart from this with Generative AI at its helm,
it aids in generating new insights, managing knowledge from vast amounts of data, making
more informed decisions, identifying new opportunities, and solving complex problems by
driving innovative pursuits.
Knowbler: The Ultimate Tool for Revolutionizing
Knowledge Management
Automates
Knowledge Creation
Enforces Top-notch
Quality with Content
Health
Presents Granular
Reports
Auto-generates Titles
and Summary
Automates Knowledge Creation
Knowbler auto-populates titles, summaries, and other facets of the knowledge articles in pre-defined
templates. This empowers employees to create and capture information at the same time, thus preventing
knowledge leakage at any touchpoint.
Key Highlights
04
BROCHURE
Auto-generates Titles and Summary
Knowbler’s integration with Large Language Models (LLMs) helps auto-generate knowledge by providing
text that summarizes large bodies of information. For example, the model can be trained on a large
collection of academic papers and then used to generate summaries of each paper, allowing researchers to
quickly review and understand the key findings of each paper.
Additionally, it leverages Generative AI to produce new article samples that are similar in style and tone.
This is done by analyzing the logged case along with its subject, description, context, and other parameters.
The model then works on generating titles and summaries based on the industry standards with an
adequate amount of title characters (60 characters), punctuations, and more.
Enforces Top-notch Quality with Content Health
It consists of an ML quality checker that gauges the content health of the article on four parameters:
uniqueness, title relevancy, link validity, and metadata. Additionally, it uses AI algorithms to recommend
related content based on their search history and behavior. This helps improve the overall value of the
knowledge base and encourages readers to explore other articles.
Additionally, its integration with Generative AI and LLMs helps boost the content health of a knowledge
article by suggesting improvements. For example, by analyzing the article and identifying areas where the
language could be clearer, more concise, or more engaging, Knowbler aids knowledge workers in making
improvements that will enhance the overall quality of the article.
Presents Granular Reports
Knowbler deploys Generative AI capabilities to present granular reports by automating the process of data
analysis and summarization and presenting it in digestible formats. It also identifies outliers or anomalies in
large datasets which can then be highlighted in granular reports like searches with no clicks, average click
position, session tracking, and more.
Additionally, the tool analyzes data from multiple sources to identify patterns and relationships that may
not be immediately apparent. This aids content creators and knowledge workers in identifying and fixing
issues whenever necessary. It also serves as a stepping stone to improve the overall credibility and
usefulness of the knowledge base.
Accelerates Knowledge Creation
Leverages KCS Recommended Templates
Drives Content Quality and Consumption
Simplifies Knowledge Sharing
Monitors Content Health with KCS Standard Checklist
Surfaces Intel on KCS Health
Encourages Faster Customer Time to Value Across KCS Journey
Measures Content Performance and Quantifies KCS Success
Knowbler has been a game-changer for many organizations, augmenting their digital capabilities,
content, and knowledge reserve. Here is one we are proud of:
Knowbler helped increase its knowledge article submission by
80% by providing relevant results with astute suggestions. It
also focused on content findability and relevance that helped
increase case deflection and expeditiously improve UX.
In order to make this experience even more seamless we are enhancing our capabilities with every new
release. So, what are the next steps?
Internally – we struggled a lot to measure the success of our content and to demonstrate, with
data, the areas where we could stand to improve, and SearchUnify solves both of those problems. If
you’re trying to implement KCS strategies into your support org, SearchUnify will help you make
your case with stakeholders, with clear case deflection metrics and actionable insights.
Peter Rittweger Content Manager, Namely
FLAGGING MECHANISM
It will allow the users to flag articles or content pieces that are outdated or
irrelevant. This ensures that the knowledge repositories are updated, accurate,
and continually evolving.
INTELLIGENT SWARMING
It is a collaborative approach to solving complex problems. With intelligent
swarming, teams are formed dynamically based on the skills and expertise
needed to solve a particular problem.
DUPLICATE ARTICLE INTIMATION
This feature will use machine learning algorithms and Generative AI to identify
and flag similar articles, ensuring that users are directed to the most relevant
and accurate information.
LINK ACCURACY (MANUAL + ML)
Knowbler plans to improve the accuracy of links in its knowledge base
through a combination of manual and machine learning-based link accuracy
checks. This will ensure that users are directed to the right information,
reducing the time and effort required to find the answers they need.
NEW VS KNOWN ANALYSIS
It will aid users in identifying gaps in their knowledge base and prioritizing areas
for improvement. By leveraging machine learning algorithms to analyze usage
patterns and user feedback, Knowbler can identify areas where new content is
needed and ensure that the knowledge base remains relevant and useful.
