The “elevator pitch” version:
I’m selling all rights to Proximatic, my fast geospatial search system.
• Fast: Remarkably high performance for many types of searches.
• Accurate: Models the earth as an ellipsoid to minimize error.
• Flexible: Supports a broad range of queries, from simple to complex.
• Easy to use: Index and search data with less than ten lines of code.
• Extensible: Clear, object-oriented design is easily enhanced and modified.
Applications include real-time analytics, ad targeting, content customization, data visualization, recommendation engines, real estate intelligence, routing, navigation, demographics, and more. Interested? Need more information? Contact me for a whitepaper!
Nine years ago, I published a little blurb about a magical place known as the McFarthest Spot, and thereafter, a slow drip of personal research on street grids, urban growth, and more. All involved the manipulation of data, mostly geographic, and, for each successive story, as a form of deliberate practice, I’d bite off slightly more than I’d previously been able to chew. Thousands of restaurant locations grew to millions of road segments to billions of Tweets, and by the end of it all, I’d authored a fairly respectable suite of geo-analytic software tools.
Around then, came a realization: out there, a universe of data described just about every spot in the world in remarkable detail. However, most of it was effectively unusable: by dint of obscurity, format, license restrictions, expense, or sheer size.
Motivated thusly, I would launch a geodata-as-a-service (GaaS) business: to unsilo all of that information, provide scalable access to it via Web API, and satisfy each query – how did people within 0.5km of (37.80766°N,122.26012°W) vote in the last Presidential election, or whatever – within a few milliseconds.
The key infrastructure? The search system, which would deftly pluck the necessary information from a sea of terabytes, many times each second, and accommodate a variety of searches, possibly on data sources that I hadn’t even discovered yet. The off-the-shelf options? Somewhat slow, too stiff, or simply inscrutable. To meet the design goals, I would have to engineer it myself.
So, I dropped my existing geo tools into a pot, stewed them for a few years in a rich broth of research, development, and deep thought, and voilà, Proximatic: my high-performance geospatial indexing and search system.
Proximatic combines a proprietary ellipsoidal geographic distance algorithm (about 6x faster and much more accurate than a typical spherical Haversine implementation), a heavily-optimized core search engine, and some novel optimizations on a recursive space-partitioning scheme to index and search large amounts of spatial data, in-memory, at blistering speed. An Amazon EC2 m5.2xlarge instance can run nearest neighbor searches on 1,000,000 randomly-distributed neighborhood-scale geocircles/georectangles in parallel at a combined rate of over 1,000,000 queries per second.From top to bottom, Proximatic is designed with flexibility and ease-of-use in mind. Work with shapes – points, lines, geocircles, georectangles, polylines, and polygons – directly, or specify a “shaper” function to easily index any type of data element without modifying its class. Run nearest, farthest, “less than distance”, “within range”, “contains” and “contained-by” searches, or assemble them into complex boolean queries with optional non-spatial filters. Leverage the “ruler” abstraction to define/order searches on the average/minimum/maximum of multiple distances, tweak a distance measurement to include non-spatial criteria (like customer ratings), or adapt the search to tolerate a certain amount of movement within the index. And more! All in a lightweight Java 8+ compatible library with a generic, object-oriented core that can be adapted to search other spaces.
Ok, super-duper… right? Well, sure, except that things change, and, for the foreseeable future, the financial risk of bootstrapping a startup probably isn’t the best choice for my family. So…
Proximatic is for sale, lock, stock, and barrel!
The buyer gets all rights to the technology: the source code, algorithms, and inventions embodied within, plus the option to develop any of the three provisional patent applications I’ve filed, or let them expire unpublished and keep Proximatic a trade secret.
Use Proximatic to improve the performance of your servers. Analyze data real-time to make decisions or target content. Optimize the embedded navigation system in your self-driving car. Feed your machine learning stack. Enhance an existing product. Or create something new.
Whatever the plan, I’m happy to assist: hire me as part of the purchase to help make it happen.
Interested? Please email me at email@example.com and I’ll send you a whitepaper with more details.