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We offer a unique, remote, global people counting solution that does not rely on any hardware and is 100% privacy compliant.
From an original idea formed during the John Lewis & Waitrose JLAB 2017 accelerator, and an MVP in the Barclays Eagle Labs Cambridge, we have evolved over the last 5 years and are now based at the world leading technology hub Level 39 in the heart of Canary Wharf.
We have been supplying footfall data for major retailers, luxury goods, restaurants, shopping malls, retail investment funds and local and central governments for over 5 years helping them to understand, optimise and create value from physical spaces.
Our software can detect footfall in almost any location anywhere in the world. Locations can be called in realtime, delivering occupancy data as a flat CSV, Interactive Dashboard or a RESTful API.
Our technology uses a unique stack of Machine Learning algorithms comprising neural networks, and using higher level mathematical models not taught in academia. All our algorithms have been coded from the ground up, not using anyone else's IP.
If physical retail stores are publicly quoted, have enough traded liquidity and the majority of the sales are store based not online, then it is possible to use our data to create predictive models to make an inference on what the equity price will be. We have over 100 equities trading that fit this criteria. We either have 3 years historic data in our data lake, or can provide a retro in a short amount of time.
As our software is written by data scientists, we provide data ready for data scientists. Either a flat file CSV or JSON for training your model through to new JSON API end point for new inferences. For visualising data sets we provide a web front end so you can check the data looks good
Even if you're not a data scientist and don't want to build models using our alternative data, using our easy to read dashboards you can quickly see trends and make investment decisions before your competitors
Our data once calibrated has been shown to be as accurate as camera data and unlike cameras you don't have to worry about the power going off, installations, people pointing them in the wrong direction. Also unlike cameras, as this is our data lake we can get footfall from any geo location worldwide
Designed by data scientists for data scientists we offer flat CSV files, JSON API, upload to AWS and everything ready to put into you own custom-built predictive model in R or Python or predictive analytics platforms like BigML or Datarobot. Contact us for our data dictionary.
Higher frequency data provides predictability for trading across asset classes. Our data can provide you with insights ahead of regulatory reporting or official government data releases.