While there are many forms and applications of AI technology, the one that is surely gaining the most traction is Generative AI. It's no wonder that generative AI is so impressive since it is capable of creating completely new and original content based on the available information.

This technology can be used to create diverse content, including text, sheets, charts, audio, video, code, images, 3D models, and more.

Around 25% of desk workers in the US reported using generative AI to assist them in daily workflow, with 80% of them reporting an increase in productivity. As time goes by, people are only finding new applications for generative AI, and the increase in productivity doesn't come as a surprise because, with the advancements in natural language processing (NLP), you essentially have a virtual assistant at hand, who can easily understand your instructions and assist you in many creative ways.

However, one important thing to note is that the results you get from generative AI will heavily depend on the quality of information it can access. This is why people find customized AIs so useful. Customized AIs are the specifically made versions of LLMs (think ChatGPT, Gemini, Copilot, and similar) that have been trained on specific sets of data with specific tasks in mind. They have been fine-tuned to respond appropriately to certain niches.

For example, if someone works in finance, the customized AI could be trained to create specific reports and spreadsheets based on the company's financial reports.

The ability to apply generative AI in a setting where users have all the relevant information and tools for their jobs led to the integration of generative AI in many software solutions, and enterprise search is no exception.

AI models perform best when trained on data directly related to their intended tasks, and while general search data may be helpful, it won't achieve the same precision as data specifically focused on what is relevant for users.

This is one of the reasons why integrating generative AI with enterprise search software makes so much sense, as it brings the power of gen AI to creatively manipulate the information together with the information that you need the most. 

How Does Generative AI Integrate with Enterprise Search?

The process begins with fine-tuning a large language model (LLM) with your company's internal data. LLMs, like Google Gemini, Microsoft Copilot, or OpenAIs ChatGPT, are incredibly complex to train and develop. This is why many software solutions integrate with established LLMs through APIs.

In essence, the API acts as a translator. It takes your company data, formats it in a way the LLM understands, and feeds it into the model for training.

Feeding the LLM with a combination of textual data (documents, emails, transcripts), structured data (databases, knowledge graphs), and contextual information (metadata, user queries) allows the LLM to grasp the specific language, terminology, and knowledge base used within your organization.

Once fine-tuned, the chosen model integrates with the enterprise search system through API and allows the employees to get:

• Direct answers: Employees can ask questions and receive answers pulled directly from your internal knowledge sources.
• Summaries: The model can generate concise summaries of relevant documents in your organization.
• Concept linking: Search results can be linked to related internal knowledge. Enterprise search systems can contextually understand and associate business-specific synonyms and respond to domain-specific queries.

Essentially, integration with existing LLMs allows enterprise search software to bring the best of generative AI directly to your business. In turn, employees can now use generative AI in a setting that is contextually relevant to their everyday tasks. That brings numerous advantages to the table, and we will now explore some.

Benefits of AI in Enterprise Search

When it comes to generative AI, there is no set-in-stone list of what it can be used for. It pretty much depends on your imagination, and with a little bit of creativity and good prompting, you can find many applications for generative AI that can drastically increase productivity and decision-making in your daily workflow.

Let's take a look at some of the benefits to give you an idea of what generative AI-powered enterprise search can bring to your business.

Generating Reports

Imagine you need to analyze sales trends for the past three years. In a traditional system, you'd:

Search for sales data for each year (22, 23, 24) - potentially across multiple applications. Then, you would download or copy the data into spreadsheets and then manually create a report with charts comparing monthly sales. This is time-consuming and error-prone.

With generative AI-powered search, you can ask a single question: "Find and analyze the company's sales data in the past three years (years 22, 23, and 24) and create a report comparing sales performance for each year month by month.”

The AI retrieves the data, understands your request, and utilizes generative AI to:

• Craft a month-by-month breakdown: It automatically generates a table showing sales figures for each month.

• Comparative analysis: It creates charts or graphs illustrating the sales trends across the months.

• Insights and highlights: It can even identify and highlight sales growth or dip patterns and potential reasons based on other data sources it finds.

This is just an example of what becomes possible once generative AI can work with the data that is relevant to you. It could also be used to aid in the creative process and marketing campaigns by answering questions like “Search the company database and find me all the New Year slogans we used in the past five years”, directly followed by the question “Find the company sales data for the 20th December to 10th of January in the past five years”.

Essentially, options are limitless, and whatever information you need, everything becomes easily available and open to analysis, which feeds employees' creative process and improves productivity.

Personalized Experience

One of the important benefits of generative AI is that it provides a personalized experience to users. Since the training of LLMs is so detailed and extensive, they are able to understand a variety of things through context.

This depends on how well the enterprise search software integrates with LLM through the API. Still, the enterprise search software that integrates thoroughly can feed the LLM all the relevant information about employees' current projects and undertakings.

This allows for generative AI that factors in users' past searches, recently opened documents, current projects, and similar data. With such data at hand gen AI can provide tailored results that are contextually relevant to what is user doing right now, and even offer personalized insight.

This means that, for example, if the user mostly focuses on sales of product X, the search results for “sales data Q3” will automatically respond with data for a specific product relevant to the user.

Understanding Context

Traditional search often focuses on exact matches – if your query doesn't include the right keywords, you get irrelevant results. Systems that are integrated with large LLMs analyze the entire sentence, recognizing synonyms and understanding the relationships between words to grasp the intent behind your query.

Imagine searching "Best quarter for shoe sales." A traditional search might just look for the word "shoe." A context-aware search understands you're looking for sales data, time periods, and a comparison, even if you didn't use those exact words.

Improved Decision-Making

Another interesting benefit to explore when it comes to cooperation between LLMs and enterprise search is the possibility of retrieving the essential information much faster.

This is especially useful in an environment with a constant influx of information, which can be overwhelming to stay on top of. Generative AI opens the possibility to go through the relevant information and offer summaries and key takeaways.

So when users ask a complex question, enterprise search will offer more than a simple list of documents; and it will also offer a summary of everything that includes the most important information for decision-making. 

This is a huge addition in a time-sensitive and information-heavy environment where informed decisions need to be made quickly.

Increased Creativity and Innovation

Enterprise search engines that integrate with generative AI expand the horizons of their users within the enterprise. They are able to show unexpected information that users might not even have been originally aware of, but that is important for the task at hand.

Once the enterprise search enables widespread availability of information, the added layer of contextual understanding enabled through technologies like vector search enables users to find connections and insights they wouldn't have discovered otherwise. With generative AI available, they can also go a step further to extract summaries, predict outcomes, and offer creative variations on existing data.

Generative AI with Akooda

Akooda's integration of predictive and generative AI allows enterprise search to transcend traditional keyword-matching. 

Enterprise search now functions as a digital knowledge analyst that understands your company's data to uncover insights and present relevant information in clear, meaningful ways. 

This combination brings the power of generative AI to your work, where you use your usual tools and programs and have access to company data. By integrating the Google LLM into your everyday workflow, Akooda allows you to apply it where you need it the most, speed up everyday tasks, and enable data-driven decision-making across your organization.