In this ever-evolving digital landscape where information should be at one’s fingertips, inefficient enterprise search remains a persistent challenge. According to IDC, a knowledge worker spends around 2.5 hours per day, or 30% of a workday, just searching for relevant information.
The information glut is scattered across various repositories, causing the traditional enterprise search system to deliver irrelevant and misleading information. This often leads to frustration and inefficiencies.
However, businesses rely heavily on information to drive decisions and innovation. And we’ve got a solution for you.
Introducing Generative AI (GenAI), a cutting-edge technology that enhances enterprise search capabilities and empowers businesses to extract value from their data labyrinths.
Wondering how GenAI is reshaping the enterprise search landscape? Check out this blog post. In it, we’ll delve into GenAI implementation in enterprise search, its use cases, and its tangible impact on businesses.
Beyond Keywords: Why Enterprise Search Needs GenAI
It’s evident that enterprise search is a cornerstone for business success, unlocking the hidden information that might be buried under the data sea. However, traditional enterprise search struggles with some limitations due to their semantic algorithms and index-based search methodologies.
Limited to Keyword Search
Traditional search systems rely entirely on exact keyword matches. For instance, a support agent is searching for information on “Bluetooth troubleshooting for Dell” to resolve a customer Gated Query. However, the traditional search might reflect a long list of irrelevant results containing the word “Dell ” only, which completely misses the support agent query intent.
As a result, support agents often spend significant time searching for relevant and accurate information, which could be invested in resolving customer queries efficiently.
Lack of Contextual Understanding
Traditional enterprise search fails to understand the border context of the user’s query, as they focus on keyword search only. It misses nuances and deeper meaning, which significantly impact the search results relevance.
Imagine a world where enterprise search comprehends the context of the user query. In this case, the search result will not be limited to keyword matches only, it understands the user query intent and delivers responses accordingly.
Limited Metadata Precision
The poor metadata makes indexing and information categorization challenging for enterprise search software. Consequently, organization knowledge suffers a lot.
Without metadata, enterprise search cannot differentiate between similar content or overlook crucial details that can enhance search results relevance. Therefore, users are forced to spend more time sifting through results, leading to frustrating user experience.
How Generative AI Transforms Enterprise Search?
GenAI acts as a catalyst that unlocks the full potential enterprise search. It is revolutionizing enterprise search in numerous ways.
Robust Intent Detection
Comprehending user query intent is imperative to deliver precise search results and GenAI thrives on it.
GenAI algorithms interpret user query context to infer intent more efficiently than traditional search. In case of vague and complex queries this next-gen technology does wonders. It helps the search system to understand the query intent is based on contextual cues, leading to more relevant and accurate search results.
Imagine one user searching for “How can I reset my password?” and another for “I forgot my password. Can you guide me?” and third for “What should I do if I fail to remember my password?” and fourth, “How can I change my password?”
Did you spot anything interesting here? Well, all queries have the same intent: to reset their password.
Semantic search understands the more profound meaning and goes beyond just keyword matching. It recognizes that all different queries have the same underlying intent.
Additionally, it deciphers that words like “reset,” “forgot,” “change,” and “retrieval” are all related to passwords. These terms will be included in the content while generating search results.
Therefore, semantic search focuses on the query’s intent and provides a more intuitive and user-friendly search experience.
Generate Answers From Single or Multiple Documents
Consider a scenario where a customer struggles to find an answer to this question, “My international wire transfer was rejected despite having sufficient funds.” This query seems complex and might not be available in a single document.
However, the customer is already overwhelmed and has to go through multiple documents to find the answer. But that’s no longer the case!
GenAI-powered enterprise search has gone beyond simple document retrieval. It understands the context of the query, searches for relevant information across all indexed data sources, and analyzes the found content documents to determine whether they are relevant to it or not. Following this, it generates a direct and coherent answer from single or multiple documents to resolve users’ queries.
Multi-lingual Support
Enterprise with multiple-lingual support is accomplished through the integration of advanced translation services and large language models (LLMs), which have been trained on diverse and massive multilingual data.
For instance, a customer enters a query in German, “Problem mit der Bluetooth-Kopplung,” which means “Bluetooth pairing issue.” GenAI can comprehend the intent and meaning behind this query, which is written in German language, find the relevant information in documents that may have been written in entirely different languages, and show accurate results.
It is not just translating utterances from one language to another, but understanding and responding to queries with their original intent.
Article Summarization
How does it feel when users do not have to read the entire article to find answers? Awesome right? GenAI-powered enterprise search has made it possible with article summarization.
A support agent received a case about a “setting up a new printer error message.” The agent will use the enterprise search to find the relevant information to resolve the customer’s query. Now, the agent has to open articles, skim through them to understand them, and then resolve the query.
However, the search engine uses GenAI to analyze the relevant knowledge-based articles and provide a concise summary highlighting the steps for the solution. By leveraging this capability,agents can resolve support cases faster, leading to increased efficiency and reduced overall support costs.
Automation and Continuous Learning
GenAI is an advanced technology which is evolving with time. By leveraging machine learning (ML), NLP and other technologies, these models are continuously learning, refining search algorithms and adapting to shifting data patterns.
This learning capability enhances the enterprise search accuracy and efficiency over time.
Implementing GenAI in Enterprise Search
GenAI implementation in enterprise is a comprehensive approach. It harnesses machine learning with domain knowledge for data analysis and personalized outcomes.
Training and Fine-tuning
Initially, GenAI models like GPT-3 are trained on massive datasets to provide broader understanding of language structure, syntax, and semantics. Later on, the model is exposed to specific industry data to decipher the specialized language and enhance its performance within that domain.
Integration with Existing Systems
Whether you leverage the open-source GenAI model or private, it is crucial that it seamlessly integrates with existing enterprise search infrastructure and offers exceptional user experience.
Effective User Training
GenAI incorporation with enterprise search is like barely scratching the surface. It’s paramount to educate users on how to use GenAI-powered search features to get the most out of it.
High Scalability
The chosen GenAI model must have flexibility to handle growing data and dynamic user demand with time.
GenAI is The Future of Enterprise Search
GenAI is a disruptive force, revolutionizing the way enterprise search delivers search outcomes. Its adhesive capability to unweave unstructured data, interpret intent and continuous learning behavior maximizes search efficiency. Additionally, it boosts employees productivity, and hastens decision-making processes.
As GenAI evolves, the future holds exciting opportunities for businesses who want to leverage this transformative technology. To see GenAI-powered enterprise search in action, request a demo now!
