Adinolfi, Allegra
(2022)
ENGINE – ENel Global INtellingent Engine.
[Laurea magistrale], Università di Bologna, Corso di Studio in
Artificial intelligence [LM-DM270], Documento full-text non disponibile
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Abstract
Engine is the newest solution developed by the Integration Platform Team that
will help Enel to manage, in the most efficient and innovative way, the document
inbound. It is a generic platform, highly configurable for all the use cases,
completely based on ML technique to recognize, classify and retrieve needed data
from specific documentation in order to automate as many processes as possible.
Engine is a novelty not only because of the AI techniques implemented but also
because it will lead people to fastly move towards a data-driven mentality that
today is crucial for such a big company like Enel. In general, the automation of
many processes that Engine is bringing and that today are still managed by
operators will definitely bring many time and economic savings. This work
describes the path faced to give life to Engine, starting from the concretization of
the idea to replace the solution as is, developing at first the business plan,
building the core component of the project giving life to the ML Models,
engineering the solution and finally monitoring the performances in production to
define what will be the next steps and challenges to face.
Abstract
Engine is the newest solution developed by the Integration Platform Team that
will help Enel to manage, in the most efficient and innovative way, the document
inbound. It is a generic platform, highly configurable for all the use cases,
completely based on ML technique to recognize, classify and retrieve needed data
from specific documentation in order to automate as many processes as possible.
Engine is a novelty not only because of the AI techniques implemented but also
because it will lead people to fastly move towards a data-driven mentality that
today is crucial for such a big company like Enel. In general, the automation of
many processes that Engine is bringing and that today are still managed by
operators will definitely bring many time and economic savings. This work
describes the path faced to give life to Engine, starting from the concretization of
the idea to replace the solution as is, developing at first the business plan,
building the core component of the project giving life to the ML Models,
engineering the solution and finally monitoring the performances in production to
define what will be the next steps and challenges to face.
Tipologia del documento
Tesi di laurea
(Laurea magistrale)
Autore della tesi
Adinolfi, Allegra
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Ordinamento Cds
DM270
Parole chiave
Engine, Enel, Machine Learining, Artificial Intelligent, solution, models, performance
Data di discussione della Tesi
22 Marzo 2022
URI
Altri metadati
Tipologia del documento
Tesi di laurea
(NON SPECIFICATO)
Autore della tesi
Adinolfi, Allegra
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Ordinamento Cds
DM270
Parole chiave
Engine, Enel, Machine Learining, Artificial Intelligent, solution, models, performance
Data di discussione della Tesi
22 Marzo 2022
URI
Gestione del documento: