Minimap.ai

Minimap.ai is a Content Cartography™ platform. Our mission is to build a literal minimap of our world's content spaces for our users. We're starting with news but we have big plans for the future.

Conception

In an age of hyperconnectivity, generative AI, and sophisticated bad actors, it’s imperative that we have the necessary context around the content we consume. Minimap.ai was founded out of extreme frustration when contemporary search engines all failed at providing any high level summary of the content being returned to us.

The current "search" paradigm is fundamentally broken. Today’s tech giants have converged on a user experience that explicitly forbids any high level understanding of the greater content space. These search engines will happily provide the best fit Wikipedia article for a query but refuse to summarize the nature of the content being returned. At its core, a summary of a Wikipedia page is very different from a summary or statistics about the available content.

This problem extends past search engines, affecting content and media platforms alike. Our goal is to build a domain agnostic platform that can clearly show users how much content is out there and how that content is distributed across a variety of topics.

What is Content Cartography™?

Content Cartography™ is a pioneering approach to navigating and understanding the vast landscape of digital information. Just as traditional cartography maps out geographical terrain, Content Cartography™ seeks to map out the expansive realm of digital content, providing users with a visual representation of the interconnected web of information available online.

At its core, Content Cartography™ involves organizing and contextualizing digital content in a way that makes it more accessible, comprehensible, and actionable for users. This involves categorizing and clustering related content into distinct regions on a digital map, allowing users to explore and navigate topics, themes, and trends with ease.

By visualizing the relationships between different pieces of content, Content Cartography™ enables users to gain valuable insights into the structure, distribution, and significance of information within a particular domain or topic area. It goes beyond mere visualization—it empowers users to interact with and manipulate the digital landscape, enabling them to customize their exploration experience based on their interests, preferences, and objectives.

Ultimately, Content Cartography™ represents a paradigm shift in how we navigate, understand, and interact with digital information. By leveraging the principles of cartography and applying them to the realm of content, Content Cartography™ offers a transformative approach to exploring the ever-expanding universe of digital knowledge, empowering users to unlock new insights, make informed decisions, and navigate the digital landscape with confidence. How Minimap.ai Works

Minimap.ai starts from the idea that in any search, there exists some number of high-level topics that are inherent to that search. From those topics, we’re able to synthesize a map of the dataspace.

Our strategy is: Topics–known and generally understood contexts–are placed on the map and serve as reference points. Content is organized with respect to the topics. Similar content should have approximately the same location on the map. That’s it!

What Can Minimap.ai Do?

Visualize the totality of some dataspace in a single view: Show where data is concentrated and where it isn’t. Color the map by content age. Height the map by content count. Our software has a natural immunity to duplicate or similar content. Duplicated content actually makes us stronger!

Highlight data: Show all search results at once. Show all posts from a single source or publisher.

Concepts

Topics

Topics are well known and familiar concepts. They’re the reference points used to understand the dataspace and contextualize the map at a high level.

For our current news dataset, we’re using a set of ~50 topics to contextualize the data.

Landscape

The landscape is created from data, where each article, each datapoint is placed as a function of how that datapoint relates to the topics. We’ve developed a proprietary strategy for aggregating massive numbers of datapoints into a single landscape such that it’s easy to see how an entire space of data is distributed.

Our approach to visualizing data lets us do some crazy things. When we display search results, we can show all of them by simply highlighting where each result falls on the map. There could be billions of results in one localized area and a single outlier out in the far reaches of the map and a user would still be able to clearly see that one datapoint amongst the billions.

Landmarks

Landmarks are familiar entities or concepts used to further contextualize the map at a low level. The placement of a Landmark is purely a function of the content associated with that entity or concept.

We've taken some of the top publishers from our dataset and given them a Landmark.

The Team

Minimap.ai was founded in December of 2022. Since then, ideas have been iterated, a team assembled, and a vision crystalized.

Clayton Smith

Founder, software and ML practitioner, general enthusiast

Melinda Cheng

Hailing from Google & YouTube, co-founder Melinda Cheng is a dynamic marketing & revenue generation executive who has advised clients such as Procter & Gamble, Walmart, and leading media & entertainment companies. Her strategic expertise will guide us to ensure that consumer & customer needs are at the core of everything we do.

Miki Herrick

Head of Legal and Operations

Linda

Head of Content and Community