If you have even a mini / micro / nano doubt about how analytics and Big Data are re-shaping this world, you should look at the list of start-ups in Y Combinator Winter 2015 batch.

What is Y Combinator?

For people who don’t know what Y Combinator is, Y Combinator is probably America’s most looked up to seed stage accelerator for tech startups. Some of the companies incubated at Y Combinator include the likes of Reddit, Dropbox and Airbnb.

The startups move to Silicon Valley for 3 months and work with Y Combinator partners to get the company into the best possible shape. At the end of these 3 months, startups present their companies to a select audience on a Demo Day. Recently, the Winter 2015 batch completed their demo day – and here is a sneak peak into how analytics is changing the world!

Analytics and Big Data based startups in Y Combinator Winter 2015 batch:

The intricacies of big data analysis compelled the team of Pachyderm to create a product that can make big data analysis simpler and doable. Their aim was to enable people who don’t know Java or Mapreduce can easily run analysis on large amounts of data. Pachyderm is an open source MapReduce engine that uses docker containers for distributed computations. It claims to have the power of MapReduce without the complexity of Hadoop.

This startup leverages data science teams to quickly transform new ideas into data driven products. They aim to create a support structure that can assist data science professionals to convert their brainstorming discussions into actionable insights. They also have a data science operation system, ScienceOps, used for managing predictive and advances decision making APIs and workflows.

This startup makes use of embedded data analytics techniques that allows a person to meet his new workout partner, a mirror. This mirror is a multi functional device. It counts the reps and sets, motivates the person to maximize reps, keeps a track of time-outs, tracks the workout progress, guides the person how to do every exercise in the best possible manner and many more functions to define.

Mashgin is automating retail checkout using computer vision. They have developed a high-precision object recognition algorithm to identify multiple items simultaneously and in any orientation. Using this technology, they have built a kiosk that aims to reduce the queues in various cafetaria.

How is MashGin solving this problem? Instead of applying neural networks and deep learning on food objects directly (which results in low precision and low recall), they first re-construct the objects in 3D and then apply their machine learning algorithms to identify the objects.

Atomwise predicts potential drug cures with the use of supercomputers, artificial intelligence and a specialized algorithm that runs through millions of molecular structures, potentially reducing the cost and time involved in making new drug discoveries. Most drug research takes months or years and millions of dollars. Atomwise utilizes AI and machine learning to enable research that costs thousands of dollars and takes just days.

They are working with companies like Merck, Notable Labs (another YC backed firm) for cancer cure, with IBM to find a cure to Ebola and with Dalhousie University in Canada to search for a measles treatment.

Kuhcoon steers fully automated, performance driven social ad-campaigns. This startup aims to inspire people to make use of their precious time into more productive tasks than wasting time on managing ad campaigns and striving for higher ROIs. Their runaway success is largely because of bringing data analytics, machine learning to use, which gave birth to data driven campaigns, programmatic optimization, automated a/b testing, live dashboard reporting, automated ad rotation . Moreover, they make use of bigdata to optimize the ad spend.

This startup says ‘What if your email app could think?’ Needless to say, by use of machine learning, slidemail automatically converts emails to calendar events. It adapts to how you use your email. It helps to sort and categorize the emails automatically. Above all, probably the best thing is, delete the app and all your data is gone with it. They don’t store any user data. As of now, it is available in App Store.

Pomello is also one of the evolving startup which makes use of a data driven approach to help companies find the right talent for their unique company culture.They undertake a survey based method to collect the data and map the team by team organizational culture and integrate it with the recruitment process.They claim to improve employee performance, lower attrition and reduce the time to hire candidates.

Streamlines hospital operations using real time optimization. analyticsMD applies machine-learning based forecasting and Industrial Engineering algorithms to anticipate demand and recommend specific actions. These actions can range from in-the-moment decisions (“Call in an additional staff member now”) to decisions that look several weeks ahead (“Adjust an appointment length”). Simply put, AnalyticsMD uses machine learning to monitor, predict, and optimize how hospitals work.

Rescue Forensics provides actionable human trafficking Intelligence. They believe that data is the future of human trafficking investigations and they use data as a tool to identify and dismantle human trafficking networks operating on the internet. their client list already includes the likes of FBI and several Police departments.

Simply by making use of data and videos, HigherMe helps various retail and service employers to find the right candidate for the job. The team of HigherMe, which involves coding wizards, employee detectives, product creators, data drivers makes this recruitment process much faster by bringing into use the latest technical expertise.

End Note:

So, there you have it! I was all pumped to see so many analytics and big data based startups coming out of Y Combinator. All of these ideas and startups are exciting and on their track to change traditional industries fundamentally or create new ones – and all of this is based on analytics and big data!

What do you think about these startups? Do you feel as pumped up as I did when I read about them first? Do share your thoughts through comments below.

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