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Artificial intelligence and big data solutions provider, Kogentix has been able to bridge that gap and deliver the quintessential solutions in this scenario. The firm integrates machine learning with distributed open source big data technologies to build applications that provide insights to clients' businesses, and make appropriate recommendations to improve KPIs and become increasingly accurate with every iteration.
Kogentix has achieved rapid growth and high customer acceptance because it is uniquely suited to help organizations address technology and business transitions. "We offer the speed, agility, and cost efficient execution of a Silicon Valley startup, with the experience, rigor, and scale to serve large established enterprises," delineates Boyd Davis, CEO & Co-founder of Kogentix.
While many firms still struggle to extract the real business value out of big data analytics, the team at Kogentix has understood the challenges and dynamics involved with the same. Much of it can be attributed to the founders at the helm of the company. Davis and his leadership team have a combined decades of experience delivering enterprise products and services for some of the industries’ most notable companies, including Intel, IBM, HP, and KPMG. This experience and expertise has helped Kogentix serve Fortune 500 companies in several verticals-- including financial services, consumer goods, healthcare, telecommunications, and industrial equipment.
Practicality Spurs Innovation
"Practical AI-fueled by big data" is the tagline of Kogentix—the central idea in the company's product design. “Trends are going to change in the next few years—away from too much focus on the exotic to a greater focus on practicality. Kogentix has always focused on practicality,” states Davis. Taking advantage of the platforms that are robust and secure, Kogentix uses industry standard tools to build applications based on distributed algorithms. The company addresses challenges from three different aspects: Data engineering skills—where the company builds and retains top engineering talent; Data science—where it develops innovative data science techniques to solve some of the most complicated customer issues and business problems; and application development—where it deploys insights gathered from data analysis into business applications.
Kogentix has achieved rapid growth and enviable customer acceptance only because it has uniquely positioned itself to help organizations take on technological and business transformations
To derive meaningful insights from large and diverse data is the prime challenge that Kogentix has set out to solve. The traditional data science approach involved taking a subset of data and applying tools such as Python and MATLAB on a local workstation. The workflows derived from this approach would be provided to a separate group who would incorporate them into applications. Cycle times were drawn out, and it was more difficult to as when input data changes demanded a recalibration of the workflow.
In the newer approach employed by Kogentix, the entire development process is integrated and iterative, and operates on the complete data available. Kogentix eliminates the hand-offs between functional silos of data engineering, data science, and line of business app developers. Kogentix delivers this integrated capability via their flagship product, the Kogentix Automated Machine Learning Platform, or AMP.
AMP incorporates a drag and drop interface with simple and intuitive application development workflow. Out of the box, AMP enables users to understand their data, and deploy one of several data science algorithms that are prepackaged with the platform, including clustering, graph, and time-series. Users can add their own algorithms and fine tune the parameters for each algorithm, making AMP a good fit for advanced data scientists. AMP can also automatically set parameters and select algorithms for best fit, enabling business analysts to create results without requiring advanced coding skills.
The final challenge is to take these insights and turn them into achievable projections and results. Davis confirms, “We have the passion for creating measurable results for our customers. We are satisfied only if the client can use our software and services to meet their goals successfully.”
Agile Methodology Meeting Customers’ Needs
Customers prefer to engage with Kogentix because the company uses open source platforms—such as Hadoop—to build data science applications. Later, depending on business needs, custom applications are built on top of the stack. This is a radically different approach because a lot of the analytics software and solutions available in the market today are designed to specific needs of the customer in a black box fashion.
AMP is a foundational platform that enables specific use cases to be delivered rapidly. Kogentix has created two templates to accelerate this process, AMP for IoT and AMP for Customer Insights. In one IoT project, a large industrial manufacturer was looking for a solution to trace its devices on the network and make them available to its customer’s as a service. Kogentix delivered solution that ingests device visibility data into a cloud hosted data platform and then uses predictive analytics to avoid unscheduled downtime. In yet another project, a large CPG manufacturer was looking to integrate retail transaction data with other selling scenarios. Kogentix delivered a solution where data science techniques were used to unearth deeper insight into sales data and delivered directly to the sales force automation tool used by sales representatives. This solution allowed a sales person, using his mobile device, to interact with retailers and find inventory details. Both the projects provided the cost saving to the individual customers. “The results in both the projects were conspicuous in their success. Every project we implement follows agile methodologies. We learn from data, as well as from our mistakes,” says Davis.
Passionate and Skilled Resources: The Secret to Success
Kogentix employs highly trained resources to build applications, and automate and streamline the development process using both professional services and value-added software. The products are developed around ideas that come from real world business needs. Many offerings in the emerging AI technology landscape have been delivered by functional experts – data scientists building better tools for data science. The Kogentix team has years of experience using technology to create business results. While their staff includes world class data engineers, architects, and PhD data scientists, their focus is on the application results, not the individual elements of technology. “The key is to integrate the strategy and business objectives with the data engineering and the data science, and to take the resulting insights and drive them into action,” explains Davis.
According to Davis, it is the appetite for innovation that drives the company ahead and rightly so. "Our customers always know their own business better than we do. In many cases, our interdisciplinary background offers tremendous value," says Davis. He continues, "What is required is a profound understanding of consumer behavior and the ability to handle complex machine data. These horizontal capabilities, coupled with a solid domain background in the vertical markets, offer the best value to customers looking to innovate." Kogentix is anticipating rapid growth in its client base across Southeast Asia, particularly in Indonesia, this year. By 2018, the company is looking forward to expanding in Europe and Latin American countries. Kogentix works on classic onshore-offshore model. Davis concludes, “We define our success when the customer is successful, and not just by delivering our technology.”