Proof before promises. Not a single unverifiable number.

Check for yourself: our robots.txt explicitly welcomes every AI crawler, each page carries validated JSON-LD, and the 2026 Barometer publishes its full methodology — queries, platforms, and how the KVS is computed.

Starting point. With only 53 reviews, a 4.1/5 rating and a #12 Google Maps position, the clinic was losing a significant share of local demand to better-rated and more visible competitors.

KAIS intervention. We implemented an automated post-appointment journey covering review requests, direct access to the Google review path, centralised patient feedback and reputation monitoring. Within 90 days, the clinic gained 231 new reviews, improved its rating to 4.8/5, reached #2 on Google Maps for the tracked local query and recorded +63% inbound calls from its Google Business Profile. We also implemented website booking and direct WhatsApp communication for promotions and reminders, creating a faster and more consistent patient communication journey.

Starting point. With 235 reviews, a 4.4/5 rating and a #27 Google Maps position, the clinic was losing a significant share of local demand to better-rated and more visible competitors.

KAIS intervention. We deployed a reusable Local Growth model combining automated post-appointment review requests, direct access to the Google review path, centralised patient feedback, reputation monitoring, web chat and local listing synchronisation. Within 120 days, the clinic gained 404 new reviews, improved its rating to 4.9/5, reached #5 on Google Maps for the tracked local query and recorded +71% inbound calls from its Google Business Profile. We also implemented a WhatsApp Bot directly on the website to add a direct patient communication channel.

Starting point. With only 28 reviews, a 3.9/5 rating and a #12 Google Maps position, the clinic was losing a significant share of local demand to better-rated and more visible competitors.

KAIS intervention. We implemented an automated post-appointment journey covering review requests, direct access to the Google review path, centralised patient feedback and reputation monitoring. Within 90 days, the clinic gained 156 new reviews, improved its rating to 4.8/5, reached #2 on Google Maps for the tracked local query and recorded +65% inbound calls from its Google Business Profile.

Starting point. The restaurant had a largely dormant customer database, low repeat-visit frequency and limited visibility for neighbourhood searches such as “restaurant [area]”.

KAIS intervention. Targeted SMS reactivation of 1,500 former customers, a short in-store QR-code journey, structured feedback collection and automated follow-up. After four months, the restaurant had recorded +310 Google reviews, generated +28% repeat visits through reactivation campaigns and reached the Top 3 Local Pack for 8 strategic keywords.

Starting point. The agency wanted to offer tradespeople, garages, hair salons and other local SMB clients a standardised reputation-led local growth solution without rebuilding the system manually for every account.

KAIS intervention. We created a reusable deployment model covering automated review requests, web chat and local listing synchronisation. Across the portfolio of 40+ SMBs, average results after 5 months showed Google ratings improving from 3.8 to 4.7/5, average Search and Maps impressions increasing by 112% per business profile, and agency client retention reaching 88%.

Starting point. BIG had an initial AI visibility score of only 25% and could not accurately identify traffic originating from ChatGPT, Perplexity, Claude and Gemini.

KAIS intervention. User-prompt auditing and purchase-intent mapping, content restructuring with direct 2–3 sentence answers at the top of key pages, deployment of FAQPage markup and server-side HTML rendering optimisation. Documented results show the AI visibility score tripling from 25% to 75%, +151% traffic from AI engines, and 2x revenue on the customer segment originating from conversational engines.

Starting point. The platform had no presence at all in AI-generated answers when legal professionals searched for the best client portal solutions.

KAIS intervention. Creation of a dedicated LLM information page, restructuring of content into question-and-answer formats that AI crawlers could extract easily, and priority targeting of high-intent Bottom-of-Funnel queries. Over nine months, the brand moved from zero presence to a dominant position across 39+ key prompts, with +20% demo bookings versus forecast and +19% organic sessions QoQ.

Starting point. The company was losing share of voice to newer competitors increasingly recommended by ChatGPT and Claude.

KAIS intervention. Implementation of the CORE — Complete Organic Revenue Engine framework, encyclopedic restructuring of the knowledge base and reinforcement of topical authority to make the brand easier for conversational engines to identify, understand and recommend across strategic topics. Over 14 months, revenue from LLM referrals increased 49x and AI referral traffic increased 26x.

Starting point. The company was heavily dependent on paid acquisition campaigns and was losing visibility as AI-generated summaries captured a growing share of the search journey.

KAIS intervention. Production of expert-written industry content to strengthen E-E-A-T, followed by deep thematic clusters targeting conversational search intent. Documented results include 7 million impressions, #1 rankings on key target queries, and a reduction of more than 75% in paid-search spend, offset by growth in AI and organic traffic.

Starting point. The company wanted to capture more qualified B2B demand through three specific query territories as a growing share of new prospects began discovering suppliers through ChatGPT answers. Qualified prospects attributable to this channel were previously close to zero.

KAIS intervention. We rebuilt the website’s semantic foundations, with particular focus on the technical product catalogue. Product imagery, use-case descriptions and technical information were reorganised to make the offer easier to understand for both buyers and machines. We reduced JavaScript-dependent delivery and replaced it with cleaner, crawler-accessible HTML, developed Entity Profiles, aligned GEO content around complex high-intent questions and created expert documents to reinforce authority. Over the last four months, this ongoing programme has generated an average of 18 qualified B2B prospects per month, compared with close to zero previously, without increasing the advertising budget.

Starting point. Despite a strong local presence in traditional Google Search, the company was barely visible in ChatGPT and Perplexity suggestions for international transport services and related queries. The objective was to develop international visibility across selected target markets.

KAIS intervention. We optimised service-page data and content around high-intent international transport searches, strengthened E-E-A-T signals to better demonstrate the company’s expertise, and reinforced third-party data sources commonly used by LLMs. We also defined strategic Question Territories aligned with the company’s commercial goals, service capabilities and target markets. Within 60 days, AI mentions increased from 0 to an average of 34+ per month, with systematic presence across the tracked recommendation answers in ChatGPT and Google AI Overviews for queries within the targeted territories.

Starting point. Despite leading in traditional Google search, the brand was nearly invisible in ChatGPT and Perplexity recommendations for specific product problems such as hair loss and frizz.

KAIS intervention. Product-page alignment around high-intent micro-categories, optimisation of presence across third-party review and product-testing platforms frequently cited by LLMs, and reinforcement of E-E-A-T signals on the brand website. Within 60 days, AI mentions increased from 86 to 282+, a 3.3x increase, with systematic presence in AI-generated buying recommendation lists.

Starting point. The company wanted to capture a growing share of shoppers using AI assistants as product search and recommendation engines.

KAIS intervention. Category-page restructuring with structured comparison tables, followed by the integration of LLM-readable product entity attributes such as materials, use cases, characteristics and comparisons. Over 5 months, revenue generated by AI-driven queries from ChatGPT, Perplexity and Claude increased 6.5x.

Starting point. Despite leading in traditional Google search, Seoul Aesthetic Central was nearly invisible in ChatGPT and Perplexity recommendations for specific skincare concerns, treatments and pathology-related queries.

KAIS intervention. We aligned treatment and service pages around high-intent micro-categories and pathology-related search intents, strengthened E-E-A-T signals on the clinic website, and improved presence across third-party review and specialist sources frequently cited by LLMs. We also mapped priority question territories aligned with the clinic’s growth objectives and deployed a Reddit authority strategy to reinforce relevant third-party discussion signals. Within 90 days, AI mentions increased from 6 to 94+, with systematic presence across tracked AI recommendation answers in ChatGPT and Google AI Overviews.

Starting point. Doctor Tim Face Clinic had a low discoverability score across LLM-generated answers and limited visibility for its priority specialties and targeted queries.

KAIS intervention. We carried out a complete restructuring and strategic organisation of the clinic’s information and data, strengthened its online reputation and expert authority, and then integrated structured data and direct-intent summaries aligned with its priority specialties and target queries. Within 4 months, the clinic’s AI Discoverability Score increased by 52%.

Starting point. The clinic team wanted to increase recommendations in LLM-generated answers across clearly defined query territories aligned with its priority dental specialties.

KAIS intervention. We strategically restructured and reorganised the clinic’s information and data to make it a more reliable citation source for LLMs, improved the website’s semantic structure, and developed expert content across relevant blogs and specialist websites. We also strengthened online reputation and expert authority, then integrated structured data and direct-intent summaries aligned with key specialties and target queries. Within six months, the clinic’s AI Discoverability Score increased by 64%. AI citations progressed from 12 during the first 45 days to 18 at the next measurement, reaching 53 in the last month.

Starting point. Zamp had a low discoverability score across AI-synthesised answers, limiting its ability to be identified and cited for relevant queries.

KAIS intervention. Removal of client-side JavaScript-dependent rendering in favour of server-rendered HTML to improve accessibility for AI crawlers, followed by the integration of structured data and direct intent summaries. In just 4 weeks, the AI Discoverability Score increased by 22%.

Starting point. The application wanted to capture users asking AI assistants high-intent comparison questions such as “What is the best alternative to [Competitor]?”

KAIS intervention. Deployment of an AEO strategy based on neutral, factual comparison matrices, supported by the publication of citable market-data studies. Over 6 months, LLM-driven conversions increased 8x and AI referral traffic increased 25x.

Starting point. The firm wanted to capture more qualified demand from complex financial queries through LLMs without increasing advertising spend.

KAIS intervention. We optimised local trust signals and entity profiles, then aligned GEO content around complex, high-intent financial queries. The programme also developed expert documents and citable resources, strengthened authority through relevant Reddit citations and discussions, and expanded digital PR and earned-media signals. Over the last 6 months, the programme has generated an average of 27 additional qualified prospects per month, with no additional advertising spend.

Starting point. The broker wanted to capture more local and regional demand from complex queries handled by Bing Copilot and ChatGPT without increasing advertising spend.

KAIS intervention. Optimisation of local trust signals and entity profiles, followed by a performance-led GEO content alignment designed to answer complex, high-intent queries more effectively. The programme generated 44 additional qualified prospects with no additional advertising spend.