We’re proud to announce today that we have opened our cloud-native Zilliant IQ Platform™ to extend its unmatched scalability and flexibility to customers looking to solve a wide range of commercial challenges tangential to pricing and sales.
Our intensive collaboration with customers on price optimization and management, predictive sales analytics and eCommerce projects revealed an opportunity for both business users and data scientists. According to Gartner, “There have been numerous recent advances in technology, process and talent development. However, an alarming percentage of models developed with the intention of full deployment are never actually operationalized. There are many reasons for this, but a crucial one is a lack of tools to enable and facilitate operationalization.”
While companies are often able to tap into open-source artificial intelligence and machine learning techniques to build data science models, they often lack a way to operationalize and deploy those models to process data at scale, automate model runs, and integrate the output of the model with other commercial systems. At a more fundamental level, simply aggregating and making sense of large volumes of data, or performing complex calculations with that data can be problematic. Many business users are forced to rely on error-prone spreadsheets to inefficiently join and process data.
B2B companies looking to solve commercial challenges can now be in the driver’s seat with the ability to create SmartApps on the Zilliant IQ Platform. The components of the Platform, underpinned by a powerful cloud-native microservices architecture, enable customers to:
- Easily integrate and analyze data within the robust, yet flexible Data Hub. Point-and-click interfaces make it simple to extend the standard data model and define new data entities. The Data Hub provides customers with ubiquitous data access and delivery capabilities at unmatched speed and scale.
- Apply the Formula Engine to execute rules and complex calculations, using an Excel-like syntax. This easily configurable capability has real-time latency and accommodates large data sets.
- Configure machine learning and data science models, including Random Forest, Neural Net, Association Rules, k-Means and Natural Language Processing. Our Prediction Engines make advanced AI/ML capabilities accessible to business users and data scientists.
- Seamlessly “bring their own model” via a Jupyter Notebook encapsulated container.
- Customize user interfaces.
- Use a configurable Job Workflow point-and-click interface to chain together various data processing components and schedule jobs in advance or on-demand.
- Integrate the model or application output with other commercial systems via high-availability, REST APIs.
Simply put, the IQ Platform represents the most unique, comprehensive and business-user friendly set of data science and AI capabilities for B2B commercial challenges, not available in any single tool on the market. It is the only cloud-native Platform with high availability, virtually unlimited scalability and agility, purpose-built for B2B companies who are facing unprecedented challenges in 2020.
“For more than two decades, our customers have trusted us to solve a wide range of problems outside of our packaged solutions,” said Zilliant President and Chief Executive Officer Greg Peters. “Offering access to the Zilliant IQ Platform is a natural next step in our relentless drive to help our customers reimagine what it takes to compete and win – now and in the future.”
Customers can now lean on the same Platform we build our pricing and sales solutions on to create their own SmartApps.
Did you say SmartApps? What’s that?
Your business is unique, so think of SmartApps as a simple way to address the unique challenges facing your business. SmartApps give you a way to operationalize data science and AI initiatives or solve unique commercial challenges that require analysis and processing of large data sets.
As an example of what is possible, some of our customers are already building SmartApps to solve for:
- Markdown Optimization – A distributor is able to quickly recommend pricing for distressed inventory.
- Milling Capacity Planning – A manufacturer is optimally matching mill capacity to customer demand.
- Cost Deviation – A distributor is predicting the likelihood of getting a deal-specific discount from a supplier.
- Competitive Price Prediction – A distributor is leveraging industry indices and prior pricing to predict competitor prices.
- Customer Potential – A food service distributor is using customer attributes like table count and cuisine type to calculate buying potential.
Get ready to think bigger, reimagine what’s possible, and leap-frog over the competition. All while drastically reducing development time and manual effort for the business.