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Latest Articles

Strategies, analysis, and perspectives on AI discoverability, GEO, and the future of how brands get found online.

  1. Foundational Concepts

    How Discoverability Engine helps Brands Asses their AI Visibility within LLMs

    Consumer’s search behaviours have shifted. From search engines, people have moved to LLMs to get their answers. To top it all, AI systems and LLMs today act as a black box, nobody really knows what answer it will give to users in return to a prompt query. What does this mean for businesses with an online presence? Discoverability Engine helps brands analyse their digital footprint and its AI visibility.

  2. Content Strategy

    Explaining C2PA Content Credentials with an Example of an Image File

    Content credentials refer to the manifest attached along with an image under the C2PA framework for content provenance. It tell us the complete history / chain of custody of the image in a tamper evident manner.

  3. GEO Strategy

    Image Metadata (EXIF, IPTC, XMP) and C2PA Provenance Content Credentials and their Importance in AI Visibility

    Image media files are not just simply visuals that we see, they carry a lot more information with them in the form of metadata. In this article we discuss EXIF, IPTC, XMP and C2PA information that comes attached with a media file.

  4. Content Strategy

    Synthetic Media Markers Have High Impact on Brand GEO and AI Visibility

    Synthetic media markers are becoming important indicators for content authenticity. LLMs and search engines do not automatically penalise content simply because it has a synthetic marker on it. Instead, synthetic media markers indicate how AI models grade brand’s credibility, content transparency and subject matter expertise, which in turn affects AI visibility.

  5. Content Strategy

    Synthetic Media Markers: How Digital Signatures and Watermarks Secure Content Provenance

    Generative AI capabilities has led to influx of synthetic content on the web. It is becoming hard to distinguish between authentic human content and AI generated content. The need for content provenance has let to synthetic media markers being actively used by companies.

  6. Technical Infrastructure

    Strategies to Improve Core Web Vitals, for Human and Agentic Experience

    Core web vitals tell us about a website’s visibility, user experience, agentic experience, conversion rates and technical infrastructure efficiency. How a website performs affects how customers perceive the brand to a great extent.

  7. Technical Infrastructure

    Core and Secondary Web Vitals: Measurement Metrics, Importance (for Humans and AI Agents)

    Core and Secondary web vitals are performance metrics standardised by google to measure the real world user experience of a web page. There are three core metrics and three secondary diagnostic metrics.

  8. Technical Infrastructure

    Page Speed for Discoverability on the Modern Web - Importance and Strategies

    Every AI agent looking for information on the web has time and token limit. If it is looking for content on the website, it has to be before the timeout of those limits. If your brand's information is not picked up within those limits, you are essentially invisible to these AI agents.

  9. Technical Infrastructure

    What Parameters AI Agents Use to Map Your Location for Contextually Relevant Results

    LLMs use direct inputs like system generated meta data (GPs location, date, time etc), context from chat memory (user profiling via past conversations), linguistic inference and tool calling techniques to decipher you location and understand the locational context of your inout query.

  10. Content Strategy

    Zero-Party Data - A Strategic Asset in Generative Engine Optimisation

    Zero-party data is the information shared by the customer intentionally through interviews, surveys, quizzes, testimonials etc. This zero-party data when used strategically has the potential of becoming a core marketing asset. Let’s learn how.

  11. Privacy and Security

    Discoverability leads to Vulnerability - Why Privacy & Security Is Essential

    Discoverability on the web essentially means optimising your website and content to be parsable, readable, citable by AI engines and bots. There was a time when we used to block bots on our website, now we have to enable them, securely, maintaining privacy of the user data and dealing with all the security loop holes which any malicious actor can exploit.

  12. Analytics

    Share of Model (SoM) is Quickly Replacing Share of Voice (SoV)

    In present day world of zero click searches and answer engines, share of model is becoming a critical strategic metric. Share of model is the percentage of times an AI answer engines like Gemini or ChatGPT mentions, cites or recommends your brand compared to your competitors for a certain query set.

  13. Foundational Concepts

    Natural Language Processing (NLP) Forms the Basis of AI Citations

    Natural language processing is the linguistics field that is responsible for interactions between computers and humans. NLP helps machines understand, interpret and generate human understandable language. NLP has enabled the large language models and answer engines based on them. Hence, understanding NLP is quite crucial to understand the discoverability on the web and build AI visibility.

  14. Foundational Concepts

    Knowledge Graphs: Brain Behind the shift from SEO to GEO to Discoverability

    Knowledge graph is a concept which has been used by google to create this massive database of facts, entities and their relationship with each other. It is not random strings of character. The objective of building knowledge graphs is for the machines to understand the world how humans do.

  15. GEO Strategy

    Generative Engine Optimisation (GEO) is the Extension of SEO With Some Key Differences

    We see a big shift from SEO to GEO for businesses which have an online presence. For decades now SEO has been the bedrock of visibility on the web. However, with LLM based answer engines we have entered a world where models like chatGPT, Gemini, Claude or perplexity synthesise information directly for the user. This big shift in the nature of how users get their information on the web has led to the emergence of the discipline of generative engine optimisation (GEO).