Cognistx begins there, inside each unique business. The Cognistx process guides a company, step-by-step, through its challenges, customer requirements, and market conditions so that an adaptive, multi-strategy AI system based on real-world objectives can be developed. “We are an AI consulting and custom solutions company, not an ‘off-the-shelf’ AI product company,” explains Eric Nyberg, PhD, co-founder and Chief Data Scientist of Cognistx. “We take a broader view on the applicability of AI on our client’s system with the expertise of our seasoned team and technology partner—Carnegie Mellon University—and work on developing highly-targeted applications.”
For every client, Cognistx conducts an in-depth data science assessment to determine ‘AI-readiness’ based on the state of their data. The objective of such an approach is to determine whether the customer’s data is clean, centralized, and normalized, making it suitable for AI adoption. If the answer is yes, Cognistx works with them to build a prototype or pilot where the organization can assess results to determine viability of further investment in the fine-tuning and deployment of the AI-system. This approach makes custom AI more practical, affordable, and accessible to small and mid-sized companies without the need for large amounts of capital to invest upfront.
In the retail world, Cognistx leverages cognitive computing to understand the behaviors, preferences, context, and trends from a set of customer data.
We take a broader view on the applicability of AI on our client’s system
In the supply chain and logistics realm, the three-year-old AI company helps organizations extract insights or abnormalities from their data using machine learning, so they can act to increase efficiency, mitigate loss, or boost their bottom line. Working with their third-party logistics client, Armada, Cognistx built an anomaly detection engine into Armada’s Electronic Data Interchange (EDI) that flags irregularities in submitted purchase orders, allowing the company to minimize costly inventory mistakes and to streamline logistical efficiency.
Because machine learning, the sub-genre of AI that is Cognistx’ specialty, relies on data which it then feeds through proprietary models trained to optimize towards a given analytic objective, Cognistx is suited to put its AI strengths to work across a variety of industries. “We focus on solving data problems to reduce cost and increase efficiency or revenue, regardless of the company,” concludes Nyberg.