Empower your company with a custom GenAI-powered search engine
Imagine having your Google-like powerhouse within your company – a digital assistant handling HR queries, locating contracts, or aiding in the reclamation process.
With GenAI-powered search engines at your fingertips, workplace efficiency takes on an entirely new dimension.
In 2024, one of the most prevalent applications of GenAI is expected to be in AI-assisted search engines. Jonas Pomoell, AI Lead Consultant at HiQ Oy, introduces HiQ employee assistant, a part of this trend:
“At HiQ Oy, we’ve developed our own HiQ employee assistant, tailored to offer insights into common practices and guidelines within our company. The rise of custom search engines, like this one, is clearly approaching, with potential applications extending to customer service and sales.”
Generative search: A brief overview
Distinguishing itself from platforms like Google, a GenAI search engine doesn’t just serve up links; it delivers actual answers to its users’ questions. Moreover, users can throw in their queries using natural language – without the need to fine-tune keywords.
“With generative AI, you can talk as you normally would when asking a question. GenAI provides a direct answer and includes a link for verification, adding a crucial layer of credibility. Remember that GenAI’s responses aren’t necessarily correct but a probabilistic outcome,” Pomoell outlines.
Another fantastic feature of GenAI assisted search engines is their impressive multilingual capabilities. Take HiQ’s Virtual Assistant, for example; even though the source data is in English, users can effortlessly communicate in Finnish or Swedish, for example. Pomoell notes that GenAI excels with most common Western languages, but its effectiveness tends to diminish the further the culture is from the US.
On a more technical level, the process involves constructing a large language model using a customized dataset. The primary objective is to create easily searchable data and then interpret the search results using GenAI. Retrieval Augmented Generation (RAG) comes into play to address a gap in how Language Models (LLMs) operate.
“RAG serves two key purposes: firstly, it assists in referencing only the primary sources of information when responding to a prompt, thereby avoiding hallucinations. Secondly, it can help the system communicate ‘I don’t know’ when it lacks an answer not found in any of the augmented sources,” Pomoell explains.
Cost management and data protection in GenAI search engines
Cost management is a fundamental aspect of most GenAI projects, given the potential for high expenses in the generative process. Interestingly, when applied to search engines, Generative AI proves to be remarkably cost-efficient.
“As the content managed by generative AI is narrowed down based on searches, it makes the method surprisingly cost-efficient. Compared to other applications of generative AI, you might even call these search engines economical,” Pomoell says.
As the content managed by generative AI is narrowed down based on searches, it makes the method surprisingly cost-efficient. Compared to other applications of generative AI, you might even call these search engines economical.
Addressing yet another common concern, Pomoell emphasizes the security of GenAI-assisted search engines. He highlights their comparability to any other secure database.
“The data stays within its database, following the protocols of any typical secure database. There’s no need for third-party transfers. Importantly, Generative AI doesn’t hold the information; it simply interprets the search results.”
Discovering business applications: Exploring use cases for GenAI search
Pomoell offers five examples illustrating how companies can integrate GenAI searches into their business, enhancing overall efficiency.
1. Enhancing efficiency and quality in customer service
In industries heavily reliant on complex policies, such as insurance and technology, customer service faces the challenge of navigating vast amounts of information to address inquiries effectively.
Here, Generative AI search comes to the rescue, analyzing customer queries, extracting relevant information, and generating synthesized responses in real-time. Once these responses are generated, they undergo human verification by customer service representatives to ensure accuracy and relevance before reaching the customer.
Moreover, companies can implement self-service with GenAI chatbots. However, it’s crucial to remember that the customer service process must be clearly defined first.
“GenAI in itself doesn’t solve problems or prompt people to use it. For example, if we want customers to prefer asking GenAI questions over sending emails, we must ensure that it is easily accessible. Many times, service design is a prerequisite for the successful application of GenAI,” emphasizes Pomoell.
2. Empowering customers and sales with generative search
Navigating through an online store with a wide range of products can be daunting for both customers and salespeople. GenAI steps in as a personal shopper – streamlining the process.
Just articulate your requirements, such as, “Show me all the red bicycles that cost under 1000 dollars and are suitable for trail,” enabling a more seamless and efficient shopping experience. Pomoell believes that GenAI will revolutionize e-commerce search functions.
“Nearly three-quarters (72%) of US retail decision-makers are ready to implement genAI technologies in 2024, according to a Google Cloud survey. While these applications vary, one highly relevant aspect is GenAI-assisted product search, similar to a knowledgeable salesperson guiding in choosing the right product. We can expect to see this trend emerging in the Nordics very soon.”
To understand how it works, Pomoell recommends giving Walmart’s generative search a look; they launched it in their online store in January 2024.
3. Simplifying product management: enhance efficiency and boost sales
Imagine you’re a manufacturer trying to make life easier for both your resellers and customers. Right now, you’ve got product info and manuals scattered across PDFs, websites, and maybe even some Excel spreadsheets. Navigating through this sea of information is like a labyrinth.
Now, picture this: with GenAI search, you can just ask what you need to know without opening file after file. The best part? You can do it in your own language. GenAI is set to decrease your customer service costs, improve the customer experience, and boost sales.
4. Effortless document management
Effectively handling numerous contracts or business proposals becomes easier with GenAI. By using a smart database, you can quickly find specific contracts based on predefined statements. For instance, you can say, “Show me all the contracts made in 2023 that include a statement of IPR rights”, or find me all the employment contracts for summer trainees”.
This not only streamlines processes but also promotes communication consistency, saving significant time and effort by identifying commonly used clauses.
5. Instant team building for developers
In consulting companies, like HiQ, building teams with specific capabilities is a constant challenge. GenAI addresses this by providing a database of experts’ CVs, enabling companies to request teams with precise expertise effortlessly. For example, one could say, “I need a team with node.js and Python expertise.”
GenAI significantly streamlines the team-building process, promoting efficiency in consulting operations.
In summary:
Generative AI revolutionizes how companies search for and interpret their documents. Even from large databases, relevant information can be found and utilized conversationally, for example, in customer service, sales, or operational enhancement. The method is surprisingly cost-effective and highly secure. Generative AI doesn’t store data; it simply interprets search results.
