Periodic Reporting for period 1 - AlchemyML (AlchemyML, The “One-Click Data-In Model-Out”)
Período documentado: 2018-08-01 hasta 2018-11-30
Learning through data will be the key aspect to compete in a dynamic environment: Machine Learning (ML) and Deep Learning (DL) are the technological trends that will allow it and will have the capability to disrupt many industries. In this context we have developed AlchemyML which main objective is speeding data management processes making Machine Learning technology accessible for all companies independently of their size and without the necessity of hiring qualified experts in this field. The objetives of the present project to make AlchemyML a global ML leader are:
• Define the product requirements
• Define a working plan
• Select adecuated technologies
• Define a commercial plan and identify regulatory requirements
• Build a business plan
• Define the product requirements
• Define a working plan
• Select adecuated technologies
• Define a commercial plan and identify regulatory requirements
• Build a business plan
To carry out this feasibility analysis we have undertaken numerous meetings in which all the staff has participated. The collaboration among people with very different profile has allowed us to coordinate the elaboration of a technical workplan with a commercial plan aligned with the technological features to be developed. We have also defined the structure of costs and revenues so that the project is profitable form the financial point of view.
The main results of this study are:
Technological
• We have selected the core technologies that we will use for the whole project-
• We have decided what algorithms and what tests must be developed
Commercial
• We will focus on Pre-processing or cleaning of data because is the most demanding activity in Machine Learning.
• We will offer Machine Learning under “as a service” scheme will bring us closer to SMEs and to other companies that are not carrying out data analysis because of the lack of experts.
• We will lay on a network of distribution partners to manage all the relationship with end-users
Financial
• AlchemyML is viable under the assumptions we believe acceptable and will generate value for shareholders
We think that is a profitable project and for that reason. We will also present this project to a SME Instrument Phase 2.
The main results of this study are:
Technological
• We have selected the core technologies that we will use for the whole project-
• We have decided what algorithms and what tests must be developed
Commercial
• We will focus on Pre-processing or cleaning of data because is the most demanding activity in Machine Learning.
• We will offer Machine Learning under “as a service” scheme will bring us closer to SMEs and to other companies that are not carrying out data analysis because of the lack of experts.
• We will lay on a network of distribution partners to manage all the relationship with end-users
Financial
• AlchemyML is viable under the assumptions we believe acceptable and will generate value for shareholders
We think that is a profitable project and for that reason. We will also present this project to a SME Instrument Phase 2.
AlchemyML is now a product that is beyond the state of the are in several aspects: is the only one that offers an end-to-end automation of the life-cycle of the data and it doesn’t require the presence of data scientists experts for its operation. These features will have the potential of disrupt the Machine Learning market bringing these technologies to all the companies, and specially to SMEs fostering their competitivity