Objectives

The primary objective of this tender is to appoint a service provider capable of developing and deploying Artificial Intelligence (AI) models for data analytics collaboration within Transnet Freight Rail. The AI models should enhance predictive and prescriptive analytics to improve asset and fleet reliability, maintenance planning, failure prevention, and operational decision-making over a period of three years.

Scope

The scope includes:

• Design, development, and deployment of AI models tailored for the rail or similar transport sectors.
• Implementation of predictive analytics solutions to optimize asset management and operational efficiency.
• Provision of training, project management, and ongoing support for the AI models.
• Integration of AI models with existing railway management systems and data infrastructure.
• Demonstration of previous AI deployments and capability to deliver within specified timelines.

Technical Requirements

The technical requirements encompass:

• Provision of evidence demonstrating previous AI model deployments in rail or similar transport sectors, including reference letters and project documentation.
• Explanation of AI model architecture and approach (e.g., machine learning, deep learning, time-series forecasting).
• Live demonstrations of AI models/platforms showing predictive improvements and operational insights.
• Integration capability with existing systems and data formats.
• Evidence of model performance metrics such as accuracy and precision.
• Compliance with data privacy, cybersecurity, and data governance standards.
• Provision of training manuals, implementation plans, and evidence of training delivery.
• Clear project plans with timelines and confirmation of previous successful implementations.

Skills Requirements

The skills and experience required include:

• Expertise in AI and machine learning model development, particularly predictive and prescriptive analytics.
• Experience in deploying AI solutions within the rail or similar transport industries.
• Proficiency in AI model architecture design, workflow automation, and data integration.
• Strong project management capabilities with proven track record in delivering AI projects on time and within scope.
• Qualified personnel with relevant engineering, data science, and project management certifications (e.g., ECSA, PMI).
• Demonstrated ability to train end-users and provide ongoing support and maintenance.