Verusen is a leading technology company that uses artificial intelligence to provide visibility, digitization and prediction of materials data and inventory for complex supply chains. Intelligent controls enforce inventory procedures to help prevent future inventory spikes, while predictive capabilities optimize allocation and procurement needs. The result is a data foundation you can trust to move quickly to innovate and support related Industry 4.0 initiatives. Verusen is venture-backed by leading investors from San Francisco to Boston, and is a Signature Company at Georgia Tech's Advanced Technology Development Center (ATDC). Verusen is a portfolio company of SAP.iO.

Verusen is a leading technology company that uses artificial intelligence to provide visibility, digitization and prediction of materials data and inventory for complex supply chains. Intelligent controls enforce inventory procedures to help prevent future inventory spikes, while predictive capabilities optimize allocation and procurement needs. The result is a data foundation you can trust to move quickly to innovate and support related Industry 4.0 initiatives. Verusen is venture-backed by leading investors from San Francisco to Boston, and is a Signature Company at Georgia Tech's Advanced Technology Development Center (ATDC). Verusen is a portfolio company of SAP.iO.

Did you miss a session from the Future of Work Summit? Managing supply chains was challenging before the pandemic, but the health crises headwinds ramped up the pressure. In a 2021 survey from the Institute for Supply Management, 42% of organizations said that increased cost to supply management due to the pandemic was one of their top concerns. A separate poll from BluJay found that outdated IT systems have become a growing barrier to supply chain innovation. One of the major blockers that organizations face when it comes to the supply chain is reconciling -- and analyzing -- information from an array of different sources. Data including images, paperwork, recordings of customer calls, and raw sensor readings are often spread across disparate systems, apps, and services that don't communicate with each other.

We have come a long way from the days when Artificial Intelligence (AI) was primarily a research project in academia or in the corporate world, and the size of the market opportunity was unclear. Today, the transformative power of AI is well recognized and the dollar value generated by AI is estimated to be at least a $3 trillion dollars annually (through sales, cost savings, automation, etc.) according to McKinsey. While academia places its focus on general AI, it has been narrow AI, which is designed to handle specific tasks, that has gained adoption and risen as a highly investable space with strong returns for customers and investors alike. On the technology side, a coalescing of trends including the pervasiveness of sensors, cheap storage and compute, and algorithmic breakthroughs have enabled the adoption of narrow AI. Another key factor for narrow or applied AI to materialize is the availability of (good) data at scale.