Quote

From:

Room 2202, 22/F,
Mega Trade Centre,
1 Mei Wan Street,
Tsuen Wan, New Territories

info@hazedawn.com
Tel: 91375571

Quote Number h-q223372036072601
Quote Date 26.07.2023
Total $1,300,000.00
To:
Global Technology Integrator Limited

Unit 3603-3609, 36/F, 1 Hung To Road, Kwun Tong, Kowloon, Hong Kong

Complaint Management System (CCMS) and improve the Consumer Council’s ability to serve consumers.
Duration : 6 Months
Objective: To leverage AI technologies to enhance the Customer

 

Hrs/Qty Service Rate/PriceAdjustSub Total
1 Complaint Management System

Develop AI and machine learning models to streamline processes, enhance data analytics capabilities, and expand the usage of the CCMS to other divisions.
Apply AI and machine learning techniques to the following areas in the new CCMS system:
1. Transcript summarization
2. Correspondence composition
3. Case classification
4. Sensitive data masking
5. Offensive language masking
6. Document completeness validation
7. Document key entity extraction
8. Data analytics and modeling

$1,300,000.000%$1,300,000.00
1 Use the following tools and models:

1. Azure AutoML for customizing and optimizing the models for your specific needs and scenarios.
2. Azure Language Service for accessing a suite of natural language processing capabilities, such as text analysis, translation, speech recognition, and synthesis.
3. Azure OpenAI gpt-35-turbo-16k for generating natural language text for transcript summarization, correspondence composition, case classification, offensive language masking, and data analytics and modeling. gpt-35-turbo-16kis a powerful and versatile language model that can adapt to various domains and tasks with minimal data and supervision.
4. Azure Form Recognizer for extracting structured data from unstructured documents, such as invoices, receipts, forms, etc. Form Recognizer can also mask sensitive data and validate document completeness.
5. PowerBI for visualizing and reporting the data analytics results in interactive dashboards and charts.
.
1. Prepare suggested volume of sample data for each AI area that need to be trained by Council for the AI models during the development stage as per AI-1 and AI-7 1.
2. Specify estimated resources required from Council in maintaining the azure openai and data training with embedding after the system launch such as update/training frequency, volume of data required, staff effort required, time required, related running cost, etc. as per AI-7 1.
3. Explore potential use of AI for the new system and ways to adapt AI growth in the future considering rapid changes in AI as per AI-7a 1.

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1 Deliverables:

1. AI and machine learning models for the specified areas that meet accuracy acceptance criteria as stated in AI-34 2.
2. Integration of the models with api services into CCMS and related components.
3. Guidelines for maintaining the AI and machine learning engine after the system launch.
4. Technical proposal specifying the suggested volume of sample data, estimated resources required and potential use of AI for the new system.

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1 Assumptions:

1. Availability of requisite data required for model development.
2. The scope may be adjusted at various stages based on feasibility and utility.

$0.000.00%$0.00
Sub Total $1,300,000.00
Tax $0.00
Total $1,300,000.00

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