When implementing a new AI system - prototyping is crucial. Questions like the following might be hard to answer in advance:
- Can the ML model solve the problem at hand?
- Is there enough data available to train the model?
- What type of model should be used to solve the problem?
However, these insights are crucial to the AI system design.
At DataArt, we believe that AI prototyping is a key foundational stage in creating successful AI solutions. With that in mind, our team developed MIA DAMA™, a framework that allows our teams to deliver results faster within a fixed time.
MIA DAMA™ stands for Management Integration and Action for Data, AI, ML, and Analytics and is inspired by the best practices of Machine Learning model Life Cycle with three sequential phases:
- Proof-of-Concept (PoC) Stage: In this phase, the team defines the client’s business objectives and AI use case, explores the data, builds the baseline model, experiments and enhances the model, builds a simple API or UI, and creates a production solution design.
- The Implementation Stage: Required to move the validated PoC into Production with scalable model deployment, external systems integration, clients’ rollout, data pipeline creation, retraining, A/B testing, and monitoring.
- The Maintenance Stage: Used for ongoing model development, improvement, monitoring, and support.
MIA DAMA™ enables DataArt to offer the initial Proof-of-Concept (PoC) stage, limited to only 6-8 development weeks, built using the best Azure AI technologies such as:
- Azure ML for data preparation, model training, and deployment
- Azure Vision for building computer vision models
- Azure Cognitive Services and Azure OpenAI to build NLP and generative AI solutions
To make the time to market even faster, DataArt's team uses proprietary accelerators, such as AutoML and Document Processing Solution, in conjunction with Azure technologies.
Additionally, PoCs will comply with Microsoft's Responsible AI practices and six main principles to ensure that the AI system is applicable for unbiased production usage.
How It Works:
After applying for this offer, our AI and ML expert team will contact you to discuss your project needs and requirements. Following the intro call, the DataArt team will create a proposal with the time, team, and budget. As soon as the paperwork is signed – the project team will start the PoC development process using the MIA DAMA™ approach, providing the client with regular updates and building the agreed deliverables.
$30,000 - $50,000, depending on the project's complexity and the scope of work.
Key Business Outcomes:
- Quick prototyping of AI solutions and hypothesis testing using the MIA DAMA™ approach
- De-risk and secure AI development within a 6-8 week timeframe
- Improved main business metrics for the selected AI use case
- Cost-effective resource allocation and project development
- A clear vision of the production solution
- The project plan, team structure, and budget will be calculated and agreed upon during the preparation project phase.
- Ready-to-use ML prototype code will be provided for future improvements.
- The ML model will be deployed on the client’s Azure cloud.
- AI solution design and integration into the production workloads and the cloud cost calculation will be described and presented.
- Potential ML use cases overview will be included to view future opportunities.
Why Choose DataArt?
We are a global software software engineering firm and a trusted technology partner of market leaders. Our uniquely human approach helps us build successful cloud, data, and AI projects for Finance, Travel, Retail, and Healthcare companies.
Our world-class AI Lab team of experts combines industry sector knowledge and ongoing AI technology research to help clients create custom software and AI solutions that improve their operations, increase revenue, and enhance customer satisfaction realizing opportunities to put clients in a leadership position.