What is conversational AI search and how does it work?

In a world dominated by AI-powered interfaces such as ChatGPT and Perplexity, expectations around how we all discover information online have changed.

Today, no one wants to sift through lists of links or guess which keyword might unlock what they’re looking for. They expect fast, accurate answers. And they want them in plain language, tailored to their needs, and available immediately. This shift is influencing how organizations think about enterprise search, giving rise to a new standard: conversational AI search built for the enterprise vs consumer AI era.

But let’s be honest: there’s a lot of noise about AI. Conversational AI search has joined the list of tools that people are starting to talk about. But how many know what it is?

If that’s a question you have, you’re in the right place. In this blog, we’ll unpack what conversational AI search is, how it works, and why it’s fast becoming a must-have for organizations focused on delivering smarter, more intuitive digital experiences — and how the Squiz conversational search advantages make this shift achievable at scale.

Conversational search is an AI-powered enterprise search tool that enables users to ask questions in natural language and receive direct, accurate answers. It mimics a human-like interaction, understanding intent and supporting multi-step queries – where users can ask follow-up questions that build on previous answers – to help users get the specific information they need, with specific answers sourced from your content.

In contrast, in traditional search, users have to phrase things in the right way, then dig through a list of links to (hopefully) find what they need. It treats each query in isolation, with no awareness of previous questions or broader intent to extend the search beyond the first query.

So while traditional search relies on keyword matching and static results, conversational AI search interprets meaning and provides contextual, human-like answers, a defining enterprise vs consumer AI difference that prioritizes governance, control, and transparency.

Traditional search vs conversational AI search

• Input: While Traditional search relies on keyword-based queries (e.g., “leave policy HR”), conversational AI search accepts natural language questions (e.g., “What’s our HR leave policy and how many days can I take?”)
• Output: Traditional search returns lists of links to documents or web pages. Conversational AI search, on the other hand, delivers a direct answer from the most relevant content, with source links for verification
• Context: Traditional search treats each query independently, without follow-up; conversational AI search maintains context across multiple questions (e.g., “What’s our leave policy?” → “How do I apply for it?”)
• User intent: Traditional search matches keywords but can miss nuance, while conversational AI search understands the meaning and goal behind the query, returning a targeted, relevant answer
• User experience: While traditional search can feel like a document dump, requiring users to open multiple links to find information, conversational AI search offers a human-like Q&A experience, similar to talking with an informed assistant

See the table below for a visual comparison.

Squiz Conversational Search uses a Retrieval-Augmented Generation (RAG) framework to generate accurate, reliable answers. It retrieves content using Squiz Funnelback’s enterprise-grade search engine that ensures only the content you want to crawl is included in the response. It then generates an answer using AI. Finally, it verifies the answer using a built-in validation step that checks responses for accuracy against your content and the question asked.

Here’s how this controlled AI search model works, step by step:

1. Smart retrieval with Funnelback: When a user submits a query, Funnelback retrieves the most relevant content from your authorized data. This includes structured and unstructured content across your site, intranet, or any other integrated systems.
2. Prompt pairing: The retrieved content is then paired with a prompt template, which controls the tone, format, and fallback behavior of the AI response (e.g., what to say when no answer is found).
3. Answer generation within your environment: The Large Language Model (LLM) selected by Squiz and hosted within Squiz’s secure DXP environment, generates an answer using your content only - never general internet data. (Note: the LLM used cannot be replaced by an alternative - Squiz has picked the best one for the job!)
4. Built-in accuracy checks: Once the system has generated an answer, it automatically runs that answer through a built-in validation step – a “faithfulness check” that verifies the generated response draws only from your approved content sources and doesn’t include any external information.
5. Response delivery with full visibility: The user receives a direct answer with source attribution and can continue the conversation naturally. These interactions can be tracked and monitored, giving you insights needed to improve the user experience.

This controlled AI search process ensures every answer is explainable, brand-safe, and traceable, qualities that clearly separate enterprise AI systems like Squiz from consumer AI tools that rely on uncontrolled data sources.

Example of this in practice:

User asks: “How do I apply for a postgraduate scholarship if I’m an international student?”

Behind the scenes, Squiz Conversational Search uses the RAG process:

1. It first retrieves relevant, verified content from your approved data sources (e.g. a postgraduate scholarships page).
2. It then augments that content and generates a plain-language answer using that content only, never from general internet data.
3. It then automatically runs the answer through a built-in validation step to check it for accuracy before it’s delivered to the user.

Squiz Conversational Search then responds:

“To apply for a postgraduate scholarship as an international student, you’ll need to complete the online application form by July 31. You must have an offer of admission and meet the eligibility requirements outlined here [link].”

This is not an AI chatbot. While the interface of conversational AI search may resemble a chatbot, the underlying technology and experience are fundamentally different. Unlike chatbots, which rely on scripted logic flows and often pull from general web knowledge, Squiz’s architecture ensures accuracy, control, and trust.

While a chatbot might handle basic FAQs or form-filling, Squiz Conversational Search is designed to understand and respond intelligently to complex user questions from within pre-defined content parameters. With enterprise-level precision and the ability to learn and improve the experience over time.

How Squiz goes beyond keyword search:

• Funnelback search engine: Enterprise-grade retrieval with support for structured and unstructured content
• Retrieval-Augmented Generation (RAG) architecture: Ensures AI only uses approved, current content
• Two-step verification process: Prevents hallucinations by verifying every answer
• Custom prompts: Tailor tone, fallback behavior, and response formatting
• Regional hosting: Keeps data sovereign and compliant (e.g. GDPR, APPs)
• Content governance tools: Track key content health indicators to ensure consistent content quality and flag outdated or risky content before it impacts search outcomes.
• Action-ready answers (coming soon): AI-generated answers don't just answer the question, they guide visitors toward the logical next step, whether that's applying, booking, downloading, or getting in touch.
  

We’ve all been there: typing the same question five different ways and still not finding what we’re looking for. As users increasingly expect intuitive, on-demand digital experiences, traditional site search often creates more friction than clarity. People can’t find what they need. Support teams spend too much time answering repeat questions. Content teams watch their work go unused.

Here is how Conversational AI search solves common pain points and the benefits generated as a result:

Challenge: Information overload, low discoverability. Users often can’t find what they’re looking for, even when the content exists. Traditional search shows a list of links, but doesn’t really guide users to where they want to or should go.

How conversational AI search solves this: It delivers direct, natural-language answers without forcing users to sift through link lists or guess the right keyword, simplifying the user journey and reducing the time users spend searching for the right answer.

Business outcome: Boosted conversions. A good conversational AI search gives users the right answer immediately, reducing friction and accelerating decision-making. Whether it’s course selection in higher education or eligibility queries in government, faster answers lead to faster actions.

Challenge: High support costs. Staff across service-led organizations spend 30% of their workday answering repetitive questions and helping users navigate complex information landscapes. Time that could be spent on higher-value work.

How conversational AI search solves this: It handles routine questions automatically, reducing the burden on staff.

Business outcome: Reduced support costs. A good conversational AI search handles common and repetitive questions 24/7, allowing your team to focus on more strategic or complex queries that truly need human input.

Challenge: Fragmented user experiences. Users have to learn different systems or know exactly where to look, leading to frustration and drop-offs.

How conversational AI search solves this: It provides one consistent way to access information across content types and platforms, guiding users with a single, intuitive interface that doesn’t require them to know where to look.

Business outcome: Better user experiences. A good conversational AI search lets users ask questions naturally and get answers no matter where the content lives, reducing drop-offs, boosting satisfaction, and building trust in your digital channels.

Challenge: Wasted content investments. Valuable information goes unused because it’s buried or too hard to access via keyword-based search. When users drop-off too early, the information is wasted.

How conversational AI search solves this: It extracts and presents the right information at the right time, ensuring users actually reach and use the resources you've invested in.

Business outcome: Improved content ROI. A good conversational AI search doesn’t let great content be wasted because it can’t be found. It makes your investment in content work harder by making it more discoverable to users.

Conversational AI search analytics also opens a window into what your users truly need. By capturing real, plain-language questions (rather than isolated keywords), you gain deeper visibility into intent, pain points, and content gaps.

Think of how a keyword-based search is structured (e.g., “leave policy HR”) versus how a question-based search is structured (e.g., “what’s our HR leave policy and how many days can I take?”). Which will give you better insights into what your user is actually after?

These insights can shape everything from your content strategy to your service design, helping teams deliver more relevant, user-focused experiences across the board.

Conversational AI search helps organizations in different sectors solve real business problems faster, smarter, and more efficiently. Below are a few examples:

Higher education

From prospective students to faculty and administrative staff, higher education institutions are navigating increasingly complex digital expectations. Conversational AI search simplifies how information is accessed and supports key goals across the student lifecycle.

Example:

User asks:“What scholarships are available for international postgrad students?”

Squiz Conversational Search responds:

“You may be eligible for the International Postgraduate Research Scholarship. Applications close July 31. Full details are available here [link].”

Other benefits:

• Students can explore programs, admissions, scholarships, and campus services using natural, conversational questions without needing to navigate fragmented sites or systems.
• Administrative burden is reduced as common queries (e.g. “When are applications due?” or “How do I apply for financial aid?”) are more easily findable via search.
• Accessibility and equity are improved by providing a consistent search experience that supports many diverse user needs, languages, and abilities. For example:
  • A student on the go can use the conversational AI tool on their phone at the campus to ask where a building is and get a fast, direct answer.
  • Someone with specific cognitive needs can ask a plain-language question and receive a simple, jargon-free response.
  • A user with vision impairment can use assistive tech like screen readers or text-to-speech to engage with the search interface naturally.

Government

Government agencies are under pressure to improve digital service delivery while maintaining transparency and compliance. Conversational AI search helps make information and services more accessible to the public.

Example:

User asks:“Am I eligible for energy bill assistance in my state?”

Squiz Conversational Search responds:

“Your state’s residents earning less than $90,000 annually may be eligible for the Energy Rebate Program. You can apply here [link].”

Other benefits:

• Citizens can find forms, services, and eligibility information quickly, without needing to understand how departments or sites are structured.
• Call center volumes are reduced as users are guided directly to what they need, available 24/7 and without the need for additional staff.
• Responses are drawn only from verified government content, ensuring consistency, transparency, and compliance with data governance requirements.

Professional services & law firms

In time-sensitive, information-rich environments like law and consulting, quick access to accurate knowledge is critical. Conversational AI search supports efficiency, client service, and business development.

Example:

User asks: “What’s the latest threshold for capital gains tax in my country?”

Squiz Conversational Search responds:

“As of FY 2024–25, individuals may be eligible for a 50% CGT discount on assets held longer than 12 months. Full details here [link].”

Other benefits:

• Lawyers and consultants can instantly retrieve relevant documents or case precedents without wasting time on manual searches.
• Business development and marketing teams gain deeper insights into what clients are searching for, fueling smarter content creation and more personalized outreach.
• Non-billable effort spent answering routine questions is reduced, improving margins and allowing experts to focus on higher-value tasks.

While the benefits are clear, it’s important to understand what’s needed behind the scenes to get the most value from it. Like any new capability, its success depends on thoughtful implementation, the right content foundation, and a clear alignment with your goals.

To support this, Squiz offers a structured consulting framework as part of our rollout. This includes strategic content assessment, configuration guidance, and hands-on support during implementation, ensuring your conversational search is tuned for performance, accuracy, and impact from day one.

For more details on this framework, read our 5-step framework guide for AI search preparation .

Implementation factors our consulting team helps you navigate:

• A strong foundation of well-structured, high-quality content is essential for best results.
• Clear expectation-setting helps users understand the scope and limitations of the tool.
• Collaboration between content and technical teams improves configuration and outcomes.
• Ongoing monitoring and tuning keep performance sharp and answers relevant over time.
• Implementation should be aligned to real user needs, not just technical goals.
• Some fine-tuning may be required to optimize specific use cases or surface the right content.

The payoff? These are the key benefits you can expect from Squiz Conversational Search:

• Faithfulness to scope: Answers are drawn strictly from your approved content – no external knowledge used.
• Accuracy: Two-step verification process helps prevent hallucinations and ensures answer fidelity.
• Control: Built-in auditing, prompt tuning, and governance tools give you oversight of every response.
• Performance: Optimized for fast response times and consistent delivery at scale.
• User experience: Feels intuitive and conversational, without needing users to learn new systems.
• Ease of use: Low-code configuration and customization options reduce reliance on technical teams.

When evaluating this intelligent search solution and whether it is right for your organization, ask yourself:

• Is the search technology accurate, relevant, and high-performing? The tool's ability to find truly relevant content is essential. No matter how smooth the conversation feels, it fails if the underlying answers are incorrect or unhelpful. Look for proven search technology with a strong track record of surfacing accurate information.
  
  Squiz meets these standards through Funnelback’s advanced retrieval engine, with a two-step verification process that ensures strict adherence to your approved sources (responses reference only your content, not external knowledge), fast response times that meet user expectations, and precise answers that directly address the question asked.

• What governance controls are available? Look for solutions that offer full oversight (auditing tools, performance monitoring, and content controls) to ensure your AI stays accurate, accountable, and on-brand.

• Is it secure, responsible, and ethically designed? Make sure the platform handles user data with care, storing queries securely, restricting access, and ensuring content is never used to train external models. Look for solutions that embed ethical AI principles from the ground up, including transparency and proper source attribution. This should be built into the system’s design, rather than an afterthought.

• Will it integrate with your existing systems? The tool should connect seamlessly with your existing content sources, authentication systems, and analytics platforms. Consider whether it can access all your relevant information, including protected internal content when appropriate.

• Can you customize the experience to match your brand? Look for the ability to tailor the conversational experience to match your brand voice, adjust response formats, and guide users toward specific actions that align with your goals.

• What analytics and insights will you get? Strong reporting features help you understand how users interact with the tool and identify opportunities to improve both the search experience and your underlying content.

In short, the key benefits of conversational AI search include:

• Faster answers: Delivers immediate, natural-language responses instead of static lists.
• Plain language understanding: Understands real questions, not just keywords.
• Contextual continuity: Maintains the thread across follow-up questions.
• Accurate and trusted: Answers are verified against approved content only.
• Reduced support load: Handles repetitive questions 24/7.
• Better insights: Surfaces actual user queries to inform content strategy.

If you're interested in understanding how Squiz Conversational Search could transform your user experience, get in touch!

Book a 30 min chat with a Squiz strategy consultant to explore how Squiz Conversational Search feature (powered by Squiz Funnelback Search) can boost engagement, improve satisfaction, and reduce support load while keeping you in full control of the experience.