Why AI Search is Hard–And How Happeo is Mastering It

The promise of AI-powered search in a company context is enticing. Imagine employees effortlessly finding the exact information they need, cutting through the clutter of outdated documents and irrelevant posts. It's a vision of boosted productivity, seamless knowledge sharing, and a more connected workforce. But the reality of AI search, particularly in the complex landscape of an intranet, is far more nuanced.

How AI Search works

Not all AI is the same. There are various types of AI models that can act as the foundation for AI functionality, with the large-language model (LLM) being among the most popular due to its deep understanding of context and human-like responses. This makes LLM a prime option, specifically, for AI search technology. 

Most AI-powered search functions on an architecture and suggested action points called Retrieval-Augmented Generation (RAG). In simple terms, the AI acts like a highly efficient librarian, following these steps:

• Retrieval: It searches your intranet and any integrated sources based on the user's query.
• Augmentation: It uses the retrieved information to formulate a response.
• Generation: It delivers that response to the user in a natural, understandable way.

Seems straightforward and the hype around AI does make it seem like a plug-and-play solution. Yet, there are some significant hurdles hidden within this process.

Data Reliability and Quality

The AI isn't a subject matter expert; it's merely an information retriever and synthesizer, a librarian, as we call it, with a vast access to information. It’s the retrieval process that helps the librarian understand what the user wants and respond with a synthesized answer. 

Its responses are entirely dependent on the quality and accuracy of the data it finds. It can't inherently determine what information is "right" or "wrong." It can only assess what exists, and then – based on user metadata and information metadata – make an educated guess about the relevance of that information.

This introduces three critical challenges:

• Inconsistent Data: If your intranet is filled with outdated policies, conflicting instructions, or disorganized information, the AI will struggle to provide reliable answers.
• Missing Data: If the knowledge your employees seek simply doesn't exist within your intranet or connected systems, the AI has nothing to work with.
• Integrate all data within the organization, and filter out relevant information.

The Perils of AI "Near Misses" and Hallucinations

One of the most frustrating aspects of AI search is the "near miss." The AI might find information that's almost right, leading to responses that appear accurate at first glance but contain subtle inaccuracies or misleading conclusions. 

Another challenge to overcome are AI “hallucinations” are when a question is asked and the AI has no reference to respond accurately, so the AI makes up what it believes to be a reasonable response. These AI "hallucinations" can erode trust in the search function and lead employees down the wrong path. It’s vital to AI Search success to be able to–instead of filling knowledge gaps with fabricated information–to identify those gaps and create correct content to enrich the AI-accessible data pool.

Incremental Approach to AI Refinement

While the ultimate solution lies in improving the underlying data, Happeo is actively working to mitigate these issues through ongoing refinements:

• Pre- and Post-Augmentation Evaluation: By assessing the retrieved information before it's used to generate a response, and then evaluating the response itself, we can be very sure about the answer quality. And we do in fact show the evaluation of the answer so you can be sure that the answer was correct.
• Retrieval Improvements: Continuous enhancements to the search algorithm help to ensure the AI retrieves the most relevant and reliable sources, reducing the chance of a "near miss."
• Contextual understanding: Understanding the user makes it easier for the retriever to find the relevant information. This includes better understanding of the user profile (title, department, past search behavior) and temporal aspect of the results, improving the answer relevancy.

• Incremental and Iterative Enrichment: Over time, as new content is introduced and additional improvements are made, it adds more context and accuracy to the underlying data.

The ultimate solution: Knowledge Engine

While these refinements help, the true key to reliable AI search is ensuring the data it draws from is accurate, complete, and up-to-date. It’s not just about data and information. Data and information are facts, but the way that that information is understood, distilled, and improved where it’s missing is how information is transformed into knowledge. 

This is why Happeo’s forthcoming Knowledge Engine is revolutionizing AI Search (and more). This sophisticated tool goes beyond traditional AI search by powering:

• Gap Detection: It proactively identifies knowledge gaps within your Happeo intranet based on user actions and provides suggested actions to the users to find information beyond search. Crucially it gathers knowledge gaps and assigns them to subject matter experts.
• Knowledge Creation: It facilitates the creation of new content to fill those gaps by using our new Pages AI and Writing Assistant.
• User Notification: It automatically informs employees who have searched for that information that it is now available via a personalized dashboard.

By actively managing and curating your intranet's knowledge base, our Knowledge Engine ensures that every employee (and AI) has access to the most accurate and up-to-date information possible–instantly and always.

The Future of AI-Powered Search

AI search is a rapidly evolving field, and Happeo is proud to be at the forefront of innovation. While challenges remain, the potential for a truly intelligent, reliable search function is within reach. By combining advanced AI with a robust knowledge management system, We are building an intranet experience that empowers employees with the information they need, precisely when they need it.