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Thought Leadership

Real-World Applications of Enterprise Search

Michal Wachstock
Written by
Michal Wachstock
Published on
August 19, 2024
Reading Time
4
Minutes
Real-World Applications of Enterprise Search
Table of contents
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Enterprise search is now widely recognized as a necessary addition for any organization that takes efficiency and information flow seriously. The need to easily search and access important information led to the development of a competitive enterprise search market that now offers dozens of established providers.

Given the competitive nature of enterprise search providers, each strives to differentiate its product with unique functionalities. This has led to a wealth of innovative features within the realm of enterprise search, leveraging its foundational role in unifying company data.

That's why we will now talk about enterprise search use cases. These use cases showcase how different organizations leverage enterprise search to solve various challenges and improve their operations.

What Can Enterprise Search be Used For?

Enterprise search has evolved well past simple information retrieval. Enterprise search used to function based on manual indexing of all company data. Now that's not necessary anymore, as the most advanced ES solutions today can work on technologies like Rapid Augmented Retrieval (RAG), based on vector similarity.

This essentially means that they don't rely on traditional indexing but are able to contextually understand and interrelate similar concepts. The search engine can retrieve all the results in its database to satisfy user intent, even if it doesn't match the keywords exactly. 

This is a significant change, as people used to need specialized skills to effectively use search engines. Now, search engines have evolved to understand and respond to human language and intent.

Enterprise search, with its comprehensive data repository, serves as an ideal foundation for numerous applications. This platform is well-suited to incorporate additional features that extract valuable insights from data, making it actionable and useful.

Today, we see a growing number of AI-powered enterprise search solutions that assist companies in:

  • Make sense of unstructured data
  • Give summaries of large datasets
  • Extract insights
  • Make workflow automations
  • Create data visualizations like graphs and pie charts
  • Help companies make data-driven decisions

These features work because the search system already has access to all company data. This means:

  • No need to set up new data pipelines or storage systems
  • Faster implementation of new features
  • Consistent data across all tools
  • Lower costs compared to buying separate tools for each function

For example, a company might use enterprise search to find all customer feedback about a product. The same system could then summarize this feedback, create charts showing common issues, and suggest improvements. All this happens using the same data, just analyzed in different ways.

Enterprise search aims to be a central hub for companies' information use. As search systems get smarter, they'll be able to do more with the data they have. This could include predicting trends, spotting patterns humans might miss, or automatically routing information to the right people.

Practical Examples of Enterprise Search in Action

Let's take a look at some common queries that employees might type into enterprise search engines to really see how they can help in daily workflow:

  • Finding the latest project information: "Latest updates on Project Phoenix" ES pulls together recent emails, documents, chat messages, and meeting notes about the project. You see the current status and recent changes all in one place.
  • Locating expertise within the company: "Who knows about GDPR compliance?" ES searches employee profiles, authored documents, and internal communications. It points you to colleagues who know about GDPR so you can get help quickly.
  • Accessing company policies: "Travel expense policy" ES instantly shows the most recent version of the policy, plus any related forms or guidelines. No need to dig through folders or ask HR.
  • Tracking document history: "Who last edited the Q2 sales report?" ES displays the document's revision history. You see who made changes and when making it clear how the document evolved and who to ask about specific edits.
  • Finding relevant training materials: "Tutorials for new CRM system" ES locates all available training resources: videos, manuals, and internal wiki pages. You quickly find what you need to learn the new system.
  • Retrieving customer information: "Latest interactions with Acme Corp" ES compiles recent emails, call logs, meeting notes, and support tickets about the customer. You get a complete picture before your next interaction.
  • Locating templates and examples: "Marketing campaign proposal template" ES finds the template and successful examples from past campaigns. You create better proposals faster by learning from what worked before.
  • Extracting insights from large datasets: "Customer complaint trends last quarter" ES can analyze thousands of customer service records and identify common issues, show which products get the most complaints, and spot any sudden spikes in problem areas. 

It's important to mention that not all enterprise search systems have all of the above-mentioned features, so do your search carefully to find the right match for your company's needs.

These examples only show some ways to use enterprise search. There are many more. As companies add AI features to their search systems, new uses come up. For example, some search systems can be used to predict future trends, write reports automatically, or suggest new product ideas based on customer feedback. Each company can find its own ways to use enterprise search based on what it needs most.

Getting Started

Akooda helps organizations make sense of their large amounts of unstructured data. It works with the tools and apps that companies already use every day, integrating smoothly with existing systems.

By combining enterprise search with AI capabilities, Akooda aims to help companies:

  1. Find information faster
  2. Understand connections between different pieces of data
  3. Get insights that might be hard to spot manually
  4. Make better use of the data they already have

Akooda's goal is to make it easier for employees to access and use the information they need without having to learn new complex systems.

If you want to see if Akooda matches your intended enterprise search use cases, book a demo and find out yourself.

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Michal Wachstock
VP Marketing
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Akooda
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