Engage in Machine learning as a Service (MLaaS) and get started with ML quickly without having to set up any specialized infrastructure nor an in-house team. Let us handle all aspects of the machine learning process and ensure maximum efficiency.
What are the benefits?
How can you use model development & hosting as a service?
Reduced development costs
Outsourcing model development can significantly reduce the cost of hiring and training in-house data scientists and engineers.
Access to expertise
Model development and hosting services often provide access to experienced data scientists and engineers, who can design and develop high-quality ML models that meet the organization's requirements.
By outsourcing model development and hosting, organizations can accelerate the time-to-market of their AI applications, allowing them to gain a competitive advantage.
By delegating the hosting of AI applications to a third-party provider, an organization can guarantee that its applications can manage a significant amount of traffic and expand in line with the organization's growth.
Model development & hosting as a service in production
We build the ML models and then you choose if we:
Deploy them to your servers: with a cost per deployment
Host them ourselves: with a pay per use model
By utilizing machine learning models, it is possible to analyze sensor data from equipment and forecast when maintenance will be required, which can help minimize downtime and enhance overall efficiency.
The analysis of sensor data from equipment can predict when maintenance is needed, reducing downtime and improving efficiency.
The evaluation of customer data can provide personalized marketing recommendations and improve customer engagement.
Image and video recognition
Images and videos analysis can identify objects, people, and scenes, improving automation and efficiency.
Natural language processing
Through the application of machine learning models, it is feasible to analyze and comprehend natural language text, leading to enhanced customer service and improved interactions with chatbots.
Steps in the process
We define the architecture and train the model.
We optimize the model for faster inference time or deployment at edge hardware.
We build a deployment strategy to avoid downtimes and have your business always operational.
Scaling accordingly to your needs, having the models 24/7 running.
We make deploying machine learning technology more approachable, scalable, and affordable.
Get in touch with one of our specialists.
Let's discover how we can help you
Training, developing and delivering machine learning models into production