Fixing small problems with big data

Almost everyone thinks big-data tools apply to ‘glamorous problems’ related to big picture strategy. At Signify we believe that big data technology works really well for ‘smaller problems’.

Here is a real example.

Modern cars run on software and testing them is difficult and time consuming. Hundreds of GB of log data and videos are generated after each test drive. Testing teams spend hours manually processing log files, and cutting videos before creating tickets for development teams.

This can take more than 2 hours per ticket.

Additionally, developers spend more time manually searching through log data to find the problems. With hundreds of tickets per car, this ‘small’ problem becomes a monster that will gladly eat all the manpower you throw at it.

Our toolchain can reduce the time per ticket from 2 hours down to a few seconds.

The data exhaust story

As engine emissions increase, the 'data exhaust' from modern vehicles continues to increase. Just like the engine exhaust tells us how the engine is performing, the data exhaust can tell us how its ‘nerves’ and ‘brain’ are functioning. It raises many questions and opportunities.

Secondly, car manufacturers first test and then launch cars into the market. This will change. In the future, highly automated cars will need continuous monitoring. This means constantly listening to what the data exhaust is saying.

Signify Chunks has answers to the data exhaust needs of today. We are also gearing up for it to become a solution for the needs of the future. A future where embedded edge computing inside a car would be combined with cloud based diagnostics.

How we got started

Back in 2012, we noticed that our friends working in the Automotive and Pharmaceutical industries were missing out on the remarkable leaps in big data technology. The software giants promised business intelligence tools with sunshine and dancing rabbits. But their focus was not on everyday problems faced by engineers and scientists.

We wanted to tackle everyday problems with new technology. In 2013, we started developing our software based on our own concept.

Most large companies back then were in the phase of evaluating the new world of “big data”. There were many different perspectives and expectations. The main problem we faced was that people did not realize the value of their data.

Selling a product in such an environment was tough. A lot of interest but no sales. Nevertheless, we continued to fund development using our own capital with no external funding. That meant tightening our belts and staying true to our vision.

Finally in October 2016, our software, Chunks, is going into production with a leading pharmaceutical giant. Chunks will analyze manufacturing IOT data on site.

Compared to other startups, we spent a lot more time on the taxiway. Nevertheless, we built the plane with our own capital and got to the runway.

You don’t need a business school degree, experience and external funds to get started. What it takes is perseverance.

So, that's our story. What's yours?