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ZeeKnows Launches LLM Visibility Package for AI Search Optimization

By Artūras Malašauskas Apr 28, 2026 4 min read Share:
ZeeKnows founder Zeeshan Yaseen introduces a 60-day package designed to increase brand citations across ChatGPT, Gemini, and Claude as AI search behavior shifts.

The search landscape is shifting beneath marketers' feet, and Zeeshan Yaseen is betting that brands need a new playbook. His agency, ZeeKnows, announced the launch of an LLM Visibility Package on April 28, 2026, targeting businesses that want to appear in responses from major large language models like ChatGPT, Gemini, and Claude.

The announcement came via GlobeNewswire, with coverage also appearing on Yahoo Finance Singapore. This is not a theoretical exercise. The package is structured as a complete, 60-day solution designed to make brands more visible, trusted, and citable across AI platforms and modern search engines.

Here's what actually happens in those 60 days. The package covers website preparation so AI systems can properly understand and reference the content. It builds credibility by listing the brand across trusted sources that AI platforms recognize. The goal is strengthening how often and how confidently the brand gets mentioned in AI-generated answers. A dedicated support manager guides the journey, and clients receive detailed progress reports. (The whole thing sounds like SEO, but for a different kind of search bar.)

Yaseen's recognition in the space precedes this launch. His work in LLM SEO has been highlighted by platforms including Indeed SEO, Triple A Review, and Rank Tracker, where he was named among the top AI and LLM SEO consultants for 2026. He has also been featured in press publications including Yahoo Finance, Tech Focus Asia, and Priority Prospect. Last year, he spoke at CMSEO, where his insights about LLM SEO drew attention from industry professionals.

The timing matters. Over the past few years, Yaseen has observed AI search evolution and recognized how rapidly user search behavior is changing. As one of the early adopters of AI and LLM SEO, he identified the gap between traditional SEO practices and the emerging need for visibility within AI systems. His main objective is helping brands unlock potential by getting cited in large language models, where users now spend most of their time searching for answers, recommendations, and solutions.

Two case studies are already attached to the package. Resimpli, an AI-powered real estate CRM provider, was one of the earliest beneficiaries. The company simplifies data management for realtors through an all-in-one AI-backed solution. It came with the clear goal of ranking in AI searches, and Yaseen turned it into reality with his LLM SEO expertise. The company is now being cited in AI search results for industry-relevant keywords, most notably "Best AI CRM for real estate investors in 2026."

Media87, a media and SEO agency in Dubai, represents another example. It had a plan to rank in AI searches and is now leveraging ZeeKnows to earn sustainable recognition in large language models. This helps diversify lead generation channels. The agency has successfully earned AI visibility for keywords like "#1 Digital Marketing Agency in Dubai 2026," and its coverage is expanding to more related queries.

Think about the physical reality of this. A user types a question into ChatGPT. They don't click through ten blue links. They get one synthesized answer. If your brand isn't in that answer, you don't exist in that moment. The LLM Visibility Package attempts to engineer that inclusion. It's less about ranking on a results page and more about being embedded in the AI's knowledge graph.

The package is positioned as a prime opportunity for brands waiting for something dependable and measurable for strategic adaptation to AI search optimization. It is designed to significantly improve brand visibility across AI platforms, regardless of company size, niche, and existing online presence. ZeeKnows focuses on constant experimentation to build strategies that take businesses to AI searches across large language models. The agency boasts multiple success stories and continues to refine methods to support AI ranking for companies across different industries, especially e-commerce, tech, and SaaS.

There are practical limitations worth noting. The package is delivered within 60 days, but AI model training cycles and knowledge cutoffs vary. What works for ChatGPT may not transfer directly to Claude or Gemini without adjustment. The case studies show keyword-specific success, but broader brand authority in AI responses requires sustained effort beyond a single package cycle. (This is not a one-and-done fix.)

Traditional SEO metrics don't fully translate here. You can't track "LLM impressions" the same way you track organic search clicks. The progress reports mentioned in the package likely measure citation frequency and keyword inclusion in AI responses, but the exact methodology remains opaque. Brands should expect to invest in ongoing optimization as models update their training data.

Whether users actually pay for this remains the real question. The package targets businesses that want to appear across major LLMs, but the ROI is harder to measure than traditional search. A brand cited in an AI answer may gain credibility, but does that translate to revenue? The case studies suggest it can, but the sample size is small. As AI search becomes more dominant, visibility in these systems will matter more. For now, early adopters like ZeeKnows are testing the waters while the rest of the industry figures out what works.

Arturas Malas Artūras Malašauskas is an AI Systems Integrator with 20+ years of production-grade web engineering experience. He has designed, shipped, and scaled enterprise Python/PHP systems for logistics, SaaS, and public-sector clients. For the past year, he has focused exclusively on AI integrations: deploying open-source LLMs, building generative media pipelines (image, audio, video), and engineering multi-agent workflows for real production environments. His standard: reproducibility, security, cost-efficient inference—no vaporware. He documents and evaluates emerging AI tooling, separating verified capabilities from marketing noise. Technical editor at: muza-ai.eu, ai-verslas.lt, ai-naujinos.lt Connect on LinkedIn
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