This report discusses the leading players in the AIoT and edgeAI platform space. With the increasing demand for AIoT and edge AI applications across industries, a need for specialised AIoT platforms is also emerging. AIoT platforms support businesses to develop, deploy, and manage AIoT solutions remotely and enable users to upgrade and modify the often containerised applications across distributed edge systems.
Typically, such a platform consists of development tools, APIs, and a library of compatible hardware devices, enabling developers to deploy ML models on AIoT devices. These platforms often incorporate features like quantisation and compression tools to optimise machine learning models to fit within the resource constraints of AIoT devices. They also monitor model behaviour by tracking and detecting drifts and degradations, re-training AI models when needed, and applying remote updates across deployed AIoT device estates.
Moreover, AIoT platform providers are widening their product offerings by partnering with various technology companies and allowing users to access software and development tools to manage ML models on AIoT devices. Businesses can gain access to a library of pre-built ML models that can be readily deployed on their fleet of devices or can provide access to industrial connectors such as MODBUS, data storage solutions such as MongoDB, and business intelligence tools for visualisation to store, process, and visualise data such as Grafana and Kibana.
