Page 561 - AI for Good Innovate for Impact
P. 561

AI for Good Innovate for Impact



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                Item         Details 
                Data Avail- The MOF IntelliServe platform uses both public and private data sources to
                ability      ensure comprehensive access to financial information.                                  4.6: Finance
                             •  Public Data:   
                                Data from publicly available sources such as government portals, public finan-
                                cial reports, and open data repositories. 
                             •  Private Data:  
                                Internal financial data from the Ministry of Finance’s secure databases, includ-
                                ing financial records, and service request history. 
                             These data sources are securely processed and integrated to ensure accurate,
                             real-time responses for users. The platform ensures compliance with data security
                             and privacy regulations. 

                Metadata     The MOF IntelliServe platform handles various types of data to ensure accurate
                (Type     of and efficient service delivery: 
                Data)        •  Text Data:    
                                Includes financial records, policies, user queries, and chatbot interactions. 
                             •  Visual Data:   
                                Scanned documents (PDFs, images), including forms, policies, and financial
                                statements processed using OCR. 
                             •  Metadata:    
                                Includes document properties like title, author, and creation date, along with
                                interaction logs such as query timestamps and user feedback. 
                Model Train- The MOF IntelliServe platform leverages the following steps for model training
                ing     and and fine-tuning: 
                Fine-Tuning   Data Collection:

                             MOF-specific data is collected and prepared to train OpenAI models for better
                             contextual understanding. 
                             Preprocessing: 
                             Data is cleaned and structured to ensure compatibility with OpenAI’s pre-trained
                             models, optimizing them for further customization. 
                             OpenAI Model Selection:
                             OpenAI’s pre-trained models are selected for their ability to handle complex
                             tasks, making them ideal for this application. 
                             Fine-Tuning: 
                             The models are fine-tuned using MOF data and hyperparameters to improve
                             accuracy and relevance in responses. 
                             Evaluation & Testing:
                             The fine-tuned models are validated using performance metrics and accuracy
                             checks to ensure optimal results. 
                             This approach ensures that the AI models are customized to meet MOF’s specific
                             needs, offering accurate and efficient performance. 
                Testbeds or  The platform is currently in full production and is actively available for the Submit
                Pilot Deploy- inquiries about the Ministry’s services. It is fully deployed and operational, provid-
                ments        ing AI-driven services to users for seamless interaction and document processing. 











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