Featuring Zilker Technology, winner of the North America Watson Build Challenge

Two years ago, we launched the IBM Watson Build Challenge, which encouraged partners from all over the world to build unique and commercial-ready solutions utilizing IBM Watson AI technology. I recently interviewed the North America Winner, Zilker Technology.

Working with IBM experts, the company developed Origin, a comprehensive solution for food tracking and payment optimization. Origin allows wholesalers, retailers and consumers to know exactly where their food came from and helps ensure that farmers are paid on time. To make Origin, Zilker Technology used IBM Watson APIs, predictive analytics, machine learning and blockchain.

I recently had a chance to interview several Zilker Technology executives. Here's what they had to share.

Tell me about Zilker Technology

Zilker Technology is a digital consultancy and systems integrator that combines the agility of a start-up with the experience and expertise of a global consulting firm. They were founded in 2014 and continue to have a large focus on IBM Cloud and Watson Customer Engagement solutions. Zilker is based in Austin, TX, and has offices in Belgrade Serbia and Chennai, India.

What made you decide to participate in Watson Build?

This is Zilker’s second year in the competition. The first year we build Z’Concierge, a framework for in-store assisted shopping by your mobile device. Our participation was such a great experience from solution discovery through delivery, that we wanted to do it again.

What are you most excited about your Watson Build solution? 

Our consultants have a lot of experience with order management, inventory management, and payment systems. We are always thinking of ways to visualize data for things like on-hand inventory and the processing time of the manufacturing, pick, pack, ship, and payment cycles. 

After we built the 3rd or 4th version, we were showing it to a test customer, and the customer was able to take our machine learning results and extract many more meanings than just the original use cases. This taught us that machine learning is really more of a baseline concept. Through iterative sessions with our customers, they will look at the data from many different angles, ask us to make tweaks, look again, tweak again. In a short time, they’re able to solve a broad range of business problems from a common baseline of data and trends. It seems so simple when you are doing it, but it’s simply another way to view the data that was always there to begin with.

Your solution helps entities along the full supply chain. How do you plan to market it?

We are working to productize our solution with the client we built it for. Once complete, we plan to market and sell to companies whose businesses depend the food supply chain in the U.S. and globally.

Has Zilker used Watson offerings for other solutions or customers? 

Yes – we’ve used Watson services for several clients. One of particular interest is a client that leverages Watson Visual Recognition to better service wind turbines. They have dramatically reduced the time of manual inspection of blades and are proactively identifying problems before they cause outages and lost revenues. 

What was the biggest challenge you faced during the process? 

Data, Data, Data. We had great test customers that were sharing data concepts, but obviously they couldn’t give us real data for a build competition like this. As a result, we had to build test data that acts like data in the real world. Since machine learning is sensitive to the quality, volume, and deviation conditions of data, it made it difficult to simulate for the competition.

Did you work together in new ways as part of this project?

The PaaS Cloud was the glue. We are a consulting services company and we have good development and delivery methodologies, but this project was using an ecosystem of services from across a very broad portfolio. This project taught us that we can bolt machine learning onto most things we do - even Blockchain!

What does the world stand to gain from this type of solution? What tangible impact could this have once implemented?

If manufacturing and supply chain companies start to adopt this solution, consumers would have a new level confidence and value in the products we use.

How has this experience inspired you to solve problems in a new way? 

This solution should set a precedent for how we can create private business consortiums. It’s difficult to create a network of business participants who are truly loyal to the larger business process. This solution created a new level of cohesion across business partners, and a reduction in friction across business entities.