In today's fast-paced technological landscape, the AEC industry is looking to leverage emerging technologies to deliver more efficient, valuable services while, at the same time, avoiding large upfront investments. Fortunately, there is a way organizations can take advantage of technological innovations without the complexities and costs associated with building solutions from the ground up: Model as a Service (MaaS).
More about MaaS
By now, we're all familiar with Software as a Service (SaaS) in which fully functional applications are accessed in the cloud and typically operate on a subscription basis. But how is Model as a Service different? MaaS platforms focus on AI-based models, hosted in the cloud and available for consumption. With a MaaS offering, users can easily integrate AI into their workflow or applications without needing to manage the underlying infrastructure. Typically offered in a pay-as-you-go system, businesses that aren't equipped to build and manage machine learning (ML) models in-house can access AI without any technical barriers. According to a recent post in DZone, MaaS "...offers a convenient and efficient way to leverage pre-trained machine learning models for specific tasks without the overhead of model development. It enables organizations to focus on their core applications instead of building models on their own."
The adoption of machine learning is much less daunting with ready-to-use models. Organizations and businesses can quickly integrate AI into their current workflows, increasing their productivity, automating repetitive tasks, enhancing decision making, and optimizing quality control processes.
Maximize AI Benefits
1) Pre-trained models. Using models that have already been trained on vast datasets to accomplish tasks provides significant time savings. No need to gather, curate, or annotate data for model training. Pre-trained models are ready to run, whenever you need them!
2) Cost savings. MaaS provides a cost-efficient entry into the world of AI. Instead of purchasing expensive software applications or high-powered computers, users only need to pay for what they use. And a MaaS platform provides users with a scalable cloud infrastructure for running AI models, reducing the need to hire expensive consultants for custom development.
3) Convenience. Organizations can focus on their core competencies with the peace of mind that their data is being used to its highest potential. Service providers of MaaS platforms are the ones who are responsible for continuous updates and maintenance, as well as security and compliance.
4) Performance. Since MaaS platforms are hosted in the cloud, models can automatically scale up or down based on usage, which ensures responsive performance. MaaS platforms are designed to handle increasing workloads and fluctuating demands by dynamically allocating resources for peak performance.
5) Flexible Integration. Models offered on MaaS platforms can also be accessible through APIs (Application Programming Interfaces), in which 3rd party applications can consume those models via API requests. This allows external companies to quickly integrate AI features into their own product offerings without needing expertise in machine learning.
Is your organization or business looking to incorporate artificial intelligence into current processes? It’s an exciting goal but the path forward may require significant time, resources and expertise.
That’s where BRYX comes in. With the powerful BRYX Model as a Service platform specifically designed for the AEC industry, you can easily access a variety of machine learning and computational models. Our BRYX models can integrate seamlessly with your existing workflows, reducing the time and effort needed to adopt AI effectively. We’re here to help you achieve your goals with a platform that’s built for your unique challenges and needs. And if you don’t see the model that you’re interested in, you can fill out our online form to request a new one! Explore the impactful and reliable ways your business can integrate AI at gobryx.com.