VentureBeat + NVIDIA + GeekSys: Startup Shootout

Could one of these dozen startups be the next Oculus?

Redshift Rendering Technologies


This sponsored post is produced by NVIDIA.

A dozen rising stars in the tech world will soon take to the stage to compete for $100,000 and a shot at glory.

It worked for Oculus. Only a year after appearing at the Emerging Companies Summit, Facebook acquired the virtual reality headset maker for $2 billion.

Each year, we talk with more innovative startups around the world that use the power of GPUs to disrupt industries and grow their business.

That’s why we created the Emerging Companies Summit. It’s a showcase for their brilliant work. And it introduces them to an audience of investors and technology execs who can open new opportunities.

The number of applicants vying for the summit’s top prize tripled this year to more than 150 companies from 30 countries. We selected the best 12, which will compete onstage in the summit’s Early Stage Challenge on March 18 in Silicon Valley.

Each CEO will have four minutes to present, plus four minutes to take questions from a panel that includes: Savitha Srinivasan, partner at IBM Venture Capital; tech pundit Rob Enderle; Saeed Amidi, founder and CEO of Plug and Play Tech Center; and Jeff Herbst, vice president of Business Development at NVIDIA.

Moderating it all will be NBC Bay Area tech reporter Scott Budman.

When they finish, the panel and audience will vote for the winner, who gets $100,000 on the spot.

Those interested in attending the event will find details here, along with a link to register. Company descriptions and presentation times are here.

The 12 competitors in next month’s Early Stage Challenge are:



(Ireland) – Deep Learning, Game Development

Today’s video games and movies require big art teams to render and create artwork. Artomatix develops tools that can automate digital media creation, allowing a single human artist to do the work of a team.

Ersatz Labs 

(U.S.) – Deep Learning, Big Data Analytics

Ersatz Labs makes a GPU-based platform for machine learning and “deep learning.” Deep learning is a type of machine learning algorithm based on the branching neuronal structure of the brain. Ersatz makes this technology practical and accessible through a web-based user interface and API.


(Germany) – Computational Fluid Dynamics, Supercomputing

FluiDyna designs and develops integrated solutions with computational fluid dynamics software for a range of customers, including vehicle manufacturers and suppliers, process and chemical engineering industries, and pharmaceutical companies.FluidDyna


(Brazil) – Computer Vision, Big Data Analytics

This award-winning startup pioneered in-store retail analytics. It has large customers in Brazil, where it is developing a single, uniform platform.


(France) – Automotive, Video and Image Processing

Intempora develops advanced driver assistance and autonomous vehicle technologies middleware. Its modular platform supports high-bandwidth data throughput from multiple sensors. It currently works with transportation, robotics and automotive companies, including Airbus, Honda and Renault.

Insilico Medicine

(U.S.) – Life Sciences, Big Data Analytics

Insilico Medicine uses genomics and big data analytics for drug discovery, drug repurposing and personalized preventative medicine. Insilico Medicine utilizes NVIDIA GPU to solve aging and age-related diseases. It also provides services to pharmaceutical companies interested in drug repurposing, early project termination, companion diagnostic development, and improving clinical trials enrollment.

NE Scientific

(U.S.) – Medical Imaging, Visualization

NE Scientific (NES) is developing new technologies for medical image analysis, modeling, and visualization. NES is sponsored by the National Cancer Institute for developing novel surgical guidance platforms for cancer treatment, is involved in projects for grading prostate cancer with magnetic resonance imaging, and in assessing the lung function in the intensive care unit using low intensity electrical fields for sensing tissues.

Pythia Systems

(Israel) – Cloud Computing and HPC, Big Data Analytics

Pythia offers a high-performance, low-cost data warehouse for analytics and reports. Its pilot project with the Israeli National Bank performed 20X faster than the bank’s data warehouse system.

QM Scientific

(U.S.) – Machine Learning, Computer Vision

QM Scientific helps consumers make smart buying decisions in real time. Consumers tell its app what they need, and the company’s platform recommends a store optimized by price, quality, shopping behavior, and location.

Redshift Rendering Technologies

(U.S.) – Rendering, Media and Entertainment

Redshift is the world’s fastest, most flexible GPU-accelerated renderer. In use today at many visual effects studios, Redshift shows that GPU-accelerated rendering offers a cost-effective, high-performance alternative to CPU rendering solutions.Redshift Rendering3

Replica Labs

(U.S.) – Computer Vision, Video and Image Processing

Turn the phone in your pocket into a 3D scanner. Replica Labs uses computer vision algorithms to quickly turn video feeds from any smartphone into accurate 3D reconstructions.


(U.S.) – Big Data Analytics, Graph Analytics, Cloud Computing

SYSTAP builds highly scalable software solutions for big graphs. Its technology can process large graphs hundreds or even thousands of times faster than competing solutions, bringing the power of high performance computing to an organization’s most time-critical graph challenges.

The Emerging Companies Summit, held Wednesday, March 18, is part of the annual GPU Technology Conference, taking place at the San Jose Convention Center in Silicon Valley from March 17 – 20. The summit provides companies with an opportunity to present their technologies to potential investors, partners, customers, analysts, and media.


Posted on 02/23/2015

Heatmaper: seeing new opportunities through spots of interest

Heatmaper is a cloud service which analyses camera recorded videos to reveal valuable insights that help marketing and trade marketing to optimize store layout, place products better and hold promotional campaigns in the "hotter" zones.

Consumer’s motion analysis in stores is one of Geeksys' big bets. It allows retailers, consultants and the well established retailing consultancies to have access to a new tool which offers visual and precise insights, without the need to install any additional equipment and in a matter of minutes.

In this article, we present a new feature for revealing the heatmaps’ visual insights with greater detail level and contextualization. In order to do so, we present an analogy.

If you have had an eye exam done or witnessed one, you probably remember the attempt of reading letters of different sizes, printed or projected on a wall, out loud. Also recall that during the exam, the eye doctor performs a number of adjustments to the lenses of the equipment, until the patient's seeing disability is minimized or completely corrected.

The Spots of interest, an exclusive Heatmaper feature, enables you to look at store areas much more clearly, just like someone who wears glasses to correct a visual impairment.


Without further ado, let’s take a closer a look at an example:

Heatmap 1: Heatmap without selected Interest Regions

*high activity index on behalf of store staff; *moderate activity index on the customer’s side

Heatmap 2: Heatmap with a selected Interest Region

*emphasis to waiting customers, through Spot of Interest / Interest Spot


The Heatmap 1, intense motion is noticeable inside the counter and moderate in the cashier line. But wouldn’t it be possible to qualify and understand consumer’s behaviour in the line better? On the Heatmap 2, there’s a selected spot of interest in the area where customers typically wait in line to pay for their purchase. In this region it’s possible to notice greater detailing on the heatmap and also extract insights such as, if you observe the red areas, the customers are waiting next to the operating cashier.


Though this is a simple example, it illustrates how it is possible to observe consumer behavior in multiple levels of detail.

But in practice, which additional insights can be extracted from interest regions? Check out some gestions / bullet points (?) on the table below:

In short, how are the Spots of interest different?


GLOBAL  Heatmap

(without interest regions)

LOCAL Heatmap

(with interest regions)


Wider way to visualize the customer’s motion in the store, focusing on identifying behavior trends.

More detailed way to look at customer’s behavior in the store, focusing on identifying specific behaviors.

Que insights posso extrair?

- “dead” regions, which customers aren’t visiting;

- regions with greater potential for promotional campaigns;

- behavior patterns and customer motion inside the store. 

- purchase intention visualization;

- behavior patterns and customer interaction with the shelf or with products directly.


Find below some examples that illustrate this amazing tool!



Like it?

How about trying Heatmaper right away?


Posted on 05/02/2014

Heatmaper: among the 5 finalists of ProXXima start-up!

ProXXima Startup has revealed the five finalists eligible to their R$20,000 prize. The awarded company will be announced this Tuesday, May 6th, on the ProXXima event, where each will have the chance to present its ideas on stage. One more company, to be selected by the event’s sponsor Mapfre this coming Saturday, May 3rd, will be presenting as well.


Check out the finalists, ranked alphabetically:


Search engine for connecting people and brands.


First Brazilian wearable: caps with RFID chips that collect information according to user behavior and distributes prizes and benefits from partners.


Platform that facilitates presentation, review and approval of pieces between agencies and clients.


Cloud service which analyses camera recorded videos to reveal customer behavior insights.


Qranio values your knowledge. Those who answer questions accumulate poins to exchange for amazing prizes. 


Heatmaper is a cloud service which analyses recorded videos to reveal valuable insights which help marketing and trade marketing to optimize store layout, product placement and holding promotional campaigns in the “hotter” zones.

Customer flow analysis in stores is GeekSys’ big bet. It allows retailers, consultants and well established retail consultancies to obtain accurate visual insights, without any additional equipment installment and in a matter of minutes. 

The offcial announcement and further information about the event can be found in: link and link


Good luck to all finalists!

Posted on 05/02/2014

Heatmaper: new looking, new features and much faster heatmaping!



The new dashboard design is now following the GeekSys' branding style.


Fully compatible with any mobile, including Android® and iOS® devices.


Heatmaper algorithms are now 25x faster, 47% more accurate and invariant to shadows and sudden light changes.


Select video periods and generate the heatmap with just 3 clicks or finger touches. (achei finger touch meio estranho! as pessoas falam assim?)

Regions of Interest

"Zoom in" and "Zoom out" on user defined scene regions to reveal details and improve the customer behaviour understanding.


Sync the uploaded video time to the real datetime for correlations between scene and in-store events.

Heatmap download

Download the heatmap image to any device with a single click or finger touch.

Video uploads

Simultaneous and drag-and-drop video uploads are now fully available.

Activity index

Easily understand how intense is the in-store customer's activity over time.


Do you want to suggest any other feature? 

We're open to listen to you, just drop us an e-mail

Posted on 04/09/2014

[Off-topic] An advise from a great entrepreneur: Elon Musk

Posted on 04/07/2014

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Make it better, not cheaper

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