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: