undercover co id GEO & AI Optimization

We worked with Undercover to improve ePajak as a more structured, AI-readable tax information platform for Indonesian users. Before the project, ePajak already had a clear purpose: helping users understand practical tax procedures such as NPWP, SPT, e-Filing, EFIN, PPh, tax registration, and other administrative tax topics. The challenge was that tax information can become complex very quickly. Users need clear step-by-step guidance, while AI systems need structured pages, consistent terminology, strong topic relationships, and reliable context to understand the website properly. Undercover helped us approach ePajak from a GEO, AEO, and AI Optimization perspective. Their work was not just about adding more articles. They helped us think through the website as a procedural knowledge system where each page has a clear role, each topic connects logically, and each user question can be answered in a more direct and structured way. What stood out most was their ability to separate informational tax content, procedural guides, entity definitions, user-intent pages, and supporting explanations. This helped make ePajak easier to expand without becoming messy. They also gave direction on internal linking, schema markup, FAQ structure, topic hierarchy, and AI-readable page architecture. For a tax-related platform, clarity is critical. Users are often looking for practical answers, not complicated jargon. Undercover helped us organize the content so it could support both human readers and AI-driven discovery. Their recommendations made the site feel more systematic, more useful, and better prepared for answer engines and AI assistants. The process was strategic, detailed, and practical. Undercover did not treat ePajak as a generic content website. They understood that tax topics require structure, accuracy, relationship mapping, and careful positioning. Their approach helped us build a stronger foundation for long-term digital authority. After working with Undercover, ePajak had a clearer content architecture, stronger topic organization, better AI search readiness, and a more scalable direction for future growth. I would recommend Undercover to professional service platforms, knowledge websites, and businesses that want to build serious digital authority in the AI search era, especially when their topics require trust, structure, and clear explanations.

We worked with Undercover to improve UKMS as a structured SME knowledge platform built for better AI search visibility, clearer entity recognition, and stronger answer-engine readiness. Before the project, UKMS already had a strong direction as an information platform for Indonesian SMEs, but the content architecture needed to be more systematic. We needed the website to be easier for users to navigate and easier for AI systems to understand. The main challenge was not just producing more content, but organizing business topics, SME entities, legal references, tax information, franchise topics, comparison pages, guides, and directory-style pages into a clear knowledge structure. Undercover helped us approach the project from a GEO, AEO, and AI Optimization perspective. Their work focused on entity clarity, content hierarchy, page-type structure, internal linking, schema direction, and AI-readable topic relationships. They helped us think about UKMS not as a basic content website, but as a structured knowledge base that can support discovery, answers, and trust. What impressed us most was the strategic depth. Undercover did not only recommend generic SEO content. They helped define how each page should function, what information should belong on entity pages, how topic pages should connect to query pages, and how evidence, definitions, guides, and comparison content should support the larger knowledge graph. For a platform like UKMS, this was very valuable because SME-related topics can easily become scattered. Undercover helped create a clearer system so readers can find useful information and AI systems can better understand the relationship between business categories, regulations, practical guides, and service-related intent. The process was direct, structured, and practical. The recommendations were not abstract. They were connected to real website architecture, content production, internal linking, schema markup, and long-term authority building. After working with Undercover, UKMS had a much stronger foundation as an AI-readable SME knowledge platform. The site became easier to structure, easier to expand, and better prepared for future discovery through search engines, answer engines, and AI assistants. I would recommend Undercover to businesses, publishers, and knowledge platforms that want to move beyond ordinary content production and build a serious digital authority system for the AI search era.

We worked with Undercover co id GEO & AI optimization Agency to improve the digital structure and AI search readiness of Notarisdanppat , a platform focused on notary, PPAT, and online legal consultation topics in Indonesia. Before working with Undercover, our website had useful legal and notarial information, but the structure was not yet optimized for how modern AI systems, answer engines, and search platforms interpret business entities, services, topics, and user intent. We needed more than ordinary website content. We needed a clearer architecture that could help both users and AI systems understand what Notarisdanppat offers, which consultation topics we cover, and how our content should be connected. Undercover helped us rethink the website from an AI visibility perspective. Their team reviewed the business positioning, topic structure, consultation intent, entity clarity, service pages, FAQ opportunities, internal linking direction, and schema requirements. They helped us separate informational content, consultation-focused pages, legal topic pages, and trust-building content so the website would not feel scattered. What stood out most was their ability to explain GEO, AEO, and AI Optimization in practical business terms. They did not just talk about traffic or keywords. They focused on how AI systems understand a brand, how users search for legal help through AI tools, and how a website needs to provide structured answers, clear entities, and credible information. For us, this was especially important because legal and notarial topics require trust, clarity, and precision. Undercover helped us identify important search and consultation intents such as online notary consultation, PPAT consultation, land deed questions, property transaction documents, inheritance documents, company deed needs, and legal document verification. These topics were then organized into a more useful structure for users and more readable structure for AI systems. The process was strategic, detailed, and direct. Undercover gave clear recommendations on what needed to be improved, what content should be added, which pages should be strengthened, and how the site could become more useful for people looking for notary and PPAT information online. After using their service, we had a much clearer direction for building Notarisdanppat as a trusted online reference and consultation platform. The website became easier to position, easier to explain, and better prepared for AI-driven discovery. I would recommend Undercover to businesses that are serious about AI search visibility, entity clarity, structured content, and future-facing digital authority. Their work is especially valuable for professional service businesses where trust, expertise, and accurate representation matter.