Machine Learning and ML Ops
Solving your data science and machine learning challenges
- Providing environments that support data exploration and wrangling as well the additional controls needed for inference in production without incurring quality issues.
- Inability to scale a model that runs effectively across a full production data set without large infrastructure costs.
- Inability to validate your machine learning model’s effectiveness against your assumptions.
- Requirements around building and deploying a cloud infrastructure to keep the total cost of ownership for ML affordable.
Make data-driven decisions and improve at scale
Download Our Capability Statement
Process
Define
We help you define the desired outcomes of your data and gain organisational alignment of how ML and ML Ops can create true business value.
Deliver
We help you successfully deliver and implement a complex machine learning program. We focus not just on the technology, but also your people, your processes, and your values to ensure that we create value for your organisation.
Deploy
Myndful deploy then test and iterate new applications, use-cases and integrations continually to maximise the value of your data and help you make smarter business decisions.
01 Define
We help you define the desired outcomes of your data and gain organisational alignment of how machine learning and ML ops can create true business value.
02 Deliver
We help you successfully deliver and implement a complex machine learning program. We focus not just on the technology, but also your people, your processes, and your values to ensure that we create value for your organisation.
03 Deploy
Myndful deploy then test and iterate new applications, use-cases and integrations continually to maximise the value of your data and help you make smarter business decisions.