Conversational AI is a fast-growing industry with a number of start-ups and established companies offering a wide variety of products and services for an even wider variety of customers. We compiled, reviewed, and curated nearly 200 companies and technologies, created one big list and categorized them in several ways to try to help understand what's taking place in the space: As we started reviewing the various companies and their offerings it became clear there were broadly two classes of offerings: those companies that offer technologies for builders: Developer Platforms vs. companies that offer products and services for enterprise end-users: Enterprise Platforms. Within the builder category, there are several types of companies most of which tend to be closer to the machine learning software itself and designed for software developers or product analysts. As mentioned in the previous blog, we found interesting domain-specific bots in the following areas: finance & insurance, health & medical, HR & recruiting, restaurants, and contact centers & customer service. Because of the volume of activity and interest in the area, we've also included sales and marketing/lead generation as another domain-specific area.

Technological change and innovation are vitally important, especially for high-tech companies. However, factors influencing their future research and development (R&D) trends are both complicated and various, leading it a quite difficult task to make technology tracing for high-tech companies. To this end, in this paper, we develop a novel data-driven solution, i.e., Deep Technology Forecasting (DTF) framework, to automatically find the most possible technology directions customized to each high-tech company. Specially, DTF consists of three components: Potential Competitor Recognition (PCR), Collaborative Technology Recognition (CTR), and Deep Technology Tracing (DTT) neural network. For one thing, PCR and CTR aim to capture competitive relations among enterprises and collaborative relations among technologies, respectively. For another, DTT is designed for modeling dynamic interactions between companies and technologies with the above relations involved. Finally, we evaluate our DTF framework on real-world patent data, and the experimental results clearly prove that DTF can precisely help to prospect future technology emphasis of companies by exploiting hybrid factors.