Challenges In Building AI Applications
Many new AI driven applications and solutions are being developed everyday. In addition, every software product and service developer is envisioning to integrate AI to make their application more intelligent. However, AI application developers are running into many challenges:
AI Model Development – The most challenging task is the development of AI models that work for all users of an application.
AI Models Performance Decays with Time – It is well known fact that the performance of AI models decays with time for a number of reasons. Today no product or technology exists that can monitor AI models and stop their decay in acceptable timeframe.
Availability of good quality training data – Another challenge to the AI development is the availability of labeled training data. Often, the training data available for AI models is insufficient or does not generalize well, resulting in their poor performance.
Robust Machines’s technologies and solutions address these challenges.
Future of AI Driven IOT Applications
AI for IOT applications has very different requirements compared to most other domains. Such applications require a very large number of AI models to achieve good performance. For example, a smart factory has many different types of machines and processes. Each unique type of machine or process will need different type of AI for predictive maintenance, anomaly detection, fault diagnosis, and bottleneck detection. If a machine is complex, we may have to model its components separately with their own AI models. The number of AI models required to manage large manufacturing organization grows exponentially. Today most vendors who are developing AI solutions for IOT, they use similar AI model design and architecture for different types of use cases. This approach results in poor performance in most cases.
RMC has developed AI4AI technology which significantly reduces the cost of AI development for IOT applications and provides the best possible performance for every use case. RMC’s AI4AI technology can auto generate good quality custom models by using use-case and device specific training data for various IOT applications. For example, RMC will auto-generate different AI models with unique architectures for predictive maintenance for different types of machines. RMC AI4AI service can also collaborate with data scientists to help improve their productivity by manyfold.
RMC ‘s products enable enterprise and IOT application and solution developers to integrate high quality AI models, and monitor and manage their performance in real time.
AI Service Center
RMC AI Service Center with its MLOPs features takes away mundane activities from data scientists and engineering, and helps enterprises integrate and manage AI in closed loop fashion in their products and services. It is also the only solution that can do real time performance management of AI models.
AI4AI Center for IOT
The AI 4 AI Center for IOT allows auto generation of data driven AI models, simplifies the integration and performance management of AI in various IOT applications, and also offers turn key AI solutions for predictive maintenance, fault diagnosis, anomaly detection, and process monitoring.
AI4AI Center for Anomalies
The AI 4 AI Center for Anomalies allows auto generation and performance management of sophisticated data driven AI models, simplifies the integration and management of AI in anomaly detection applications such as cyber threat detection, fraud detection, and defect detection for manufacturing.
RMC’s product and platforms are based on innovative technologies that have allowed us to monitor the performance of AI models in real time, as well as automatically generate solution centric AI.
“To raise new questions, new possibilities, to regard old problems from a new angle, requires creative imagination and marks real advance in science.”
Solution Partners & Supported Integrations
RMC supports or planning to support integration with all key EAM/CMMS solution vendors and IOT platforms.
Discover The Future
We are pioneers in integrating AI in a scalable fashion for Enterprise and IOT applications.