AI Search and the Future of Digital Discoverability with Alex Casals

As AI search is expected to handle 50% of queries by 2028, companies must fundamentally rethink how they get discovered online. Alex Casals shares how his team built Tac

mind to help brands track their visibility in AI-generated answers and optimize their content strategy for this new conversational search landscape.

Alex Casals is a Barcelona-based founder who recently launched Tacmind, an AI search visibility platform, after identifying a critical gap while running his previous company, Taclia. As an all-in-one software for SMEs, Taclia's team developed internal tools to track how their brand appeared in AI-generated search results. When other startups showed intense interest in these capabilities, Alex recognized an opportunity to serve companies navigating the shift from traditional SEO to AI-driven discovery.

The conversation explores how AI search is fundamentally changing digital marketing and discoverability. Alex explains that companies can no longer rely solely on traditional SEO strategies as users increasingly turn to conversational AI interfaces instead of clicking through Google results. This shift creates both challenges and opportunities for brands trying to maintain visibility in an evolving search landscape.

For B2B SaaS teams managing multilingual content and international expansion, this episode offers practical insights into tracking brand mentions across AI platforms, identifying high-authority citation sources in different regions and languages, and optimizing website structure for conversational search. Alex shares specific technical recommendations and strategic approaches that help companies adapt their content strategies for AI-powered discovery.

Episode 50, Broken Down

Use this timeline to jump to the topics most relevant to your multilingual content, localization, and global growth challenges.

00:04:03 – 00:05:34

The Fundamental Shift in Search Behavior Discussion of how AI search is expected to handle 50% of queries by 2028, forcing companies to rethink digital marketing strategies. Alex explains the two-pronged approach: optimizing third-party citations and restructuring owned websites for conversational search.

00:05:42 – 00:08:41

How Tacmind Works: Tracking AI Visibility

Alex provides a detailed walkthrough of Tacmind's functionality, explaining how companies define prompts relevant to their business, track daily positioning in AI answers, monitor competitors, and identify citation sources that influence AI-generated responses.

00:09:00 – 00:14:19

Strategic Advice for Tech Leaders

Alex shares recommendations for founders adapting to AI search, emphasizing the importance of visibility assessment, understanding citation sources, and making technical website changes to support conversational discovery.

00:14:19 – 00:17:19

Citations and Content Strategy

Discussion of how citation strategy differs from traditional SEO, the renewed importance of PR and media mentions, and opportunities in niche blogs that have strong authority in AI systems despite lower traditional traffic.

00:17:19 – 00:19:26

Multilingual and Regional Considerations

Alex explains how Tacmind handles different regions and languages, emphasizing that prompts and results vary significantly across markets and cannot simply be translated, requiring localized content strategies.

00:19:26 – 00:22:34

Organizational Mindset and Measurement Discussion of how marketing teams need to evolve their technical capabilities, the importance of accepting rapid change, and how AI search visibility can be measured faster than traditional SEO with daily tracking and clear action plans.

00:22:34 – 00:25:49

Creative Applications and Final Advice

Alex shares creative use cases including B2B teams using retail shop mentions to identify sales opportunities, and closes with his core advice: content remains the most critical investment for brands navigating AI search.

Key Discussion Areas

The Shift from Traditional SEO to AI Search Visibility

AI search is fundamentally changing how users discover information, with expectations that AI will handle 50% of search queries by 2028. This shift creates anxiety for companies that have invested heavily in traditional SEO, as users increasingly prefer conversational AI interfaces over clicking through traditional search results. The change represents both a challenge to existing strategies and an opportunity for companies willing to adapt early.

As AI search evolves, traditional ranking tactics fall short—brands need an LLM SEO blueprint to understand how large language models parse and prioritize content.

Companies must now focus on two parallel strategies: optimizing third-party citations (media, blogs, forums where AI systems find information) and restructuring their own websites to be more conversational and easily parsed by AI. The traditional focus on driving clicks is being replaced by a focus on being accurately represented in AI-generated answers.

Why this matters for B2B SaaS and localization:

• Understand how to assess current brand visibility in AI-generated search results before competitors gain advantage

• Learn the two-pronged approach of optimizing both third-party citations and owned website structure

• Recognize that early movers can gain measurable advantages as AI search adoption accelerates

• Adapt content strategies before traditional SEO investments become less effective

Citation Sources and Content Distribution Strategy

In AI search, citations—the sources where AI systems find information about brands—become critically important. Unlike traditional SEO where companies focused primarily on their own domain authority, AI search elevates the importance of third-party mentions in media, blogs, and niche publications. Interestingly, smaller niche blogs with strong topical authority can be as valuable as major media outlets for specific prompts.

This shift revitalizes the importance of PR and content distribution strategies that some companies had deprioritized. Companies need to identify which specific sources AI systems cite for their relevant prompts, then strategically pursue mentions in those sources. The challenge is that these valuable citation sources often vary by region, language, and specific topic, requiring sophisticated tracking to identify opportunities.

Successful global content strategies go beyond translation. Learn how strategic localization strengthens your presence in diverse markets and supports discoverability.

Why this matters for B2B SaaS and localization:

• Discover high-authority niche blogs and sources that may be under your radar but influence AI answers

• Understand why PR and media mentions are gaining renewed strategic importance despite declining direct traffic

• Learn to identify citation opportunities that competitors may not have discovered

• Develop targeted content distribution strategies based on actual AI citation patterns rather than assumptions

Technical Website Optimization for Conversational Search

Websites must be restructured to support conversational AI search rather than traditional keyword-based search. This includes making URL structures more explicit and descriptive (e.g., /products/non-alcoholic/ instead of generic paths), adding comprehensive FAQ sections to every landing page, and making content more conversational rather than relying on visual design elements that AI cannot parse.

The goal is to make it easier for AI systems to understand what a company offers, who it serves, and how it differs from competitors. This often means being more explicit and repetitive than traditional web design principles would suggest, as AI systems need clear, text-based information rather than relying on visual hierarchy or user interface elements.

Why this matters for B2B SaaS and localization:

• Implement specific technical changes to URL structure and content organization that improve AI discoverability

• Add FAQ sections strategically to every landing page to support conversational search patterns

• Make website content more explicit and conversational to help AI systems accurately represent your offerings

• Understand that visual design elements and contact forms don't help AI understand your value proposition

Multilingual and Regional AI Search Strategies

AI search visibility varies dramatically across regions and languages, requiring localized strategies rather than simple translation. The prompts users ask, the sources AI systems cite, and the competitive landscape all differ by market. Companies cannot simply translate English prompts and expect the same results in German, Italian, or Spanish markets.

Effective multilingual AI search strategies treat each language-region as its own ecosystem, with tailored prompts and citation tracking rather than a simple one-to-one translation. This mirrors how modern localization workflows are shifting—language strategy is no longer just about translating strings, but about orchestrating AI, tools, and content processes that reflect real user search behavior in each market. By treating markets as unique and building workflows that understand local search patterns and context, companies uncover underserved opportunities and ensure their global content is both discoverable and relevant.

Why this matters for B2B SaaS and localization:

• Recognize that AI search strategies must be localized, not just translated, for each target market

• Identify potential low-hanging fruit opportunities in specific language-region combinations

• Understand how to structure tracking and optimization efforts across multiple markets

• Learn why working with translation services helps identify actual search patterns in each language

Measuring and Accelerating AI Search Performance

Unlike traditional SEO which can take 3-6 months to show results, AI search visibility can be tracked daily with clear metrics. Companies can see their position in AI-generated answers, monitor competitor mentions, track citation sources, and measure changes in response to optimization efforts. This faster feedback loop enables more agile strategy adjustments.

The measurement approach includes tracking brand mentions across relevant prompts, monitoring which competitors appear in answers, identifying citation sources, and receiving automated recommendations for content improvements. While achieving top positioning still requires sustained effort (especially against established competitors), companies can see progress and validate strategies much faster than with traditional SEO.

Why this matters for B2B SaaS and localization:

• Track AI search visibility daily rather than waiting months for traditional SEO results

• Receive specific, actionable recommendations based on actual citation patterns and competitive positioning

• Identify quick wins through citation opportunities and content gaps

• Monitor competitor strategies and citation sources to inform your own approach

Highlights & Insights

Key takeaways for B2B SaaS teams working on multilingual content, localization, and international expansion:

• AI search is expected to handle 50% of queries by 2028, requiring companies to fundamentally rethink digital marketing and discoverability strategies

• Companies need a two-pronged approach: optimizing third-party citations (where AI finds information) and restructuring owned websites for conversational search

• Citation sources matter more than ever—niche blogs with topical authority can be as valuable as major media outlets for specific prompts

• Website URL structure should be explicit and descriptive (e.g., /products/non-alcoholic/) to help AI systems understand offerings

• Add comprehensive FAQ sections to every landing page, not just a general FAQ page, to support conversational search patterns

• Make website content more conversational and explicit rather than relying on visual design elements that AI cannot parse

• AI search strategies must be localized for each region-language combination, not simply translated from English

• PR and media mentions are gaining renewed importance despite declining direct traffic, as AI systems cite these sources

• AI search visibility can be tracked daily with clear metrics, providing faster feedback than traditional SEO's 3-6 month timeline

• Content investment remains critical—technical website changes and citation strategies both depend on high-quality, strategic content

• Companies can track competitor positioning and citation sources to identify opportunities and inform strategy

• Creative applications exist beyond traditional marketing, such as B2B teams using retail shop mentions to identify sales opportunities

AI Search Makes Multilingual Content Strategy a Growth Lever

The shift to AI-powered search doesn’t just change how companies are discovered—it raises the bar for how clear, consistent, and localized their content needs to be. As Alex highlights, being visible in AI-generated answers depends on two things: strong, authoritative citations across the web and content that AI systems can truly understand. And both become exponentially more complex once you operate across multiple languages and markets.

This is exactly where multilingual content stops being a translation task and becomes a growth strategy.

At Undertow, we help B2B SaaS companies structure, localize, and scale their content so it works in every market they care about. From making landing pages more conversational, to ensuring consistency across languages, to adapting content for regional search behavior, the goal is the same: helping brands show up accurately and credibly wherever their future customers are searching.

As AI search accelerates, companies that invest early in high-quality, market-aware multilingual content won’t just keep up—they’ll gain a durable visibility advantage. And in a world where AI answers replace clicks, being understood is the new competitive edge.