We help our customers to apply machine learning strategy to the real business problems by providing a full stack of services: from discovery and research through models building and prototyping to integrating the production-ready solution into a business process.
This is how it works:
1. Opportunities identification and problem definitions.
We usually run a session with relevant key people in the company to understand what data our customers have and what problems they need to solve. In other words, we try to figure out if there is a way to use Machine Learning / AI to help a customer make more money or reduce looses All options are open.
2. Scoping and Validation.
Not all the ideas are equally valuable for the business, also not all the ideas are equally eligible for implementation. Some require more effort, other require more data. We analyze whether the effort meets value expectations and whether the customer has enough data for that. In some cases data could be obtained from other sources or augmented.
3. Researching and Prototyping.
At this step we run experiments to come up with model(s) that will become the core of the solution. Model(s) will be used to create proof of concept of a real business flow to reflect value.
4. Software Architecture & Design.
If we reached this point, it means that the model(s) have proved to be valuable and it's time to turn them into a product. At this stage we design how the existing product feeds and consumes the AI-solution, or define the software design of a new product built based on this solution.
5. Product Development.
We develop APIs to integrate with the existing product or build a completely new product as designed in previous step. To learn more about this process.
Whether you're considering, planning or already implementing AI in your venture, talk to us, we're friendly.
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