AI phases

Our goal is to provide solutions driven by cutting-edge AI technology that lead the industry in precision and ease-of-use. Our solutions are successful because of close work with our clients, our experienced team, and a well-prepared set of tools.

Working with Data.Monsters:

We aim to help companies with different AI maturity. We start with initial assessment and finish with valuable product tailored to the needs of our customers.

AI readiness assessment
In-depth review of your AI maturity, business data readiness, and potential use cases.

Delivery a roadmap on how to implement AI projects based on current ideas and their feasibility analysis
Start a project on a specific use case

Our proof of concept saves your time and money while demonstrating tangible business value and helping to pilot and scale properly
Pilot / Scaling
We help the business to realize potential fully and earn money, not try innovations.

That is why we can be in charge of full implementation (softwareengineering, algorithm optimization, and interface design)

1. Don't expect AI to solve everything.

Spend some time to understand what AI can or cannot do, given your limitations of engineering resources, data, or technology for a particular use case. Technical diligence, in addition to business diligence, is crucial for selecting feasible and valuable AI projects.

2. Don't scale AI specialists too fast.

ML people are a scarce resource, but they can be useful only if business talents know how to work with them. Teams have to be cross-functional to find feasible and valuable projects.

3. Don't expect AI project to work the first time fully.

AI development is often an iterative process, so it is essential to manage expectations in your organization. Business people should be aware of an iterative process with multiple attempts needed to become a big story for your business.

4. Don't apply traditional planning processes without changes.

The types of timeline estimates, milestones, and deadlines, and KPIs or OKRs associated with AI projects are a bit different than the same things related to non-AI projects.

5. Don’t expect you can wait with AI start 

Your second AI project would be better than your first. Your third AI project would better than your second. The first project starts building a competitive advantage for the future until your competitors implement all critical use cases.

AI mastery
We can provide end-to-end solutions thanks to our partnerships with top US hardware providers and integrators
Over 70 projects
We’ve had >70 clients in the last 5 years in Manufacturing, Electronics, and Healthcare with a total impact estimation of more than $200 mln
Worldwide presence
We are distributed team of  70 top data scientists (12 PhD) in multiple university areas in the United States, Europe, and Asia.
Focus on business
We are business people by nature, and we know how to combine data science talents and real-life operations to help your business