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The Delhi Metro Rail Corporation has initiated a process to develop an AI-driven project management system aimed at improving planning, monitoring and execution of metro infrastructure works. The system will rely on historical project data to predict delays, optimise schedules and monitor compliance through automated checks. DMRC has invited startups to jointly develop the platform under a shared-cost model, with incentives of INR 20 lakh and shared intellectual property rights. Proposals are being evaluated, with deployment planned in phases after development and testing.
The Delhi Metro Rail Corporation (DMRC) has moved to introduce an artificial intelligence-based project management system designed to address long-standing challenges in managing large and complex metro infrastructure works. The proposed platform is intended to move beyond conventional software tools that primarily track milestones and flag delays, by actively supporting planning, execution and decision-making across project stages. Advertisement
DMRC has invited startups to collaborate on the development of an Agentic AI-based Project Management System, selecting partners through a competitive innovation-driven process rather than a traditional tender route. The initiative will be implemented through memorandums of understanding, under which development costs will be shared, and responsibilities clearly divided between the metro operator and the technology partner.
The proposed system will use historical data from past metro projects to build more accurate schedules, identify risks at an early stage, and suggest corrective actions during execution. It will be designed to dynamically adjust timelines in response to site-level conditions such as manpower availability, equipment performance and external disruptions, helping project teams respond faster to emerging issues.
In addition to scheduling, the AI platform will monitor the use of materials, machinery and labour in real time. Automated document analysis will be used to identify missing approvals, incomplete inspections and potential regulatory gaps, reducing dependence on manual checks. Site monitoring will be strengthened through AI-enabled drones and cameras that compare actual progress with approved designs and construction plans.
DMRC has outlined that the system will integrate multiple AI agents with existing project management and building information modelling tools. These integrations are expected to generate consolidated dashboards, daily progress reports, predictive alerts and compliance updates through digital workflows. The scope also includes communication modules, request-for-information tracking, inspection management, document control, cybersecurity safeguards and computer vision-based progress analysis.
Eligible startups will be required to present their solutions before an expert committee, following which up to three participants may be shortlisted for development and hosting of the platform on DMRC's servers for a six-month period. Based on performance and evaluation, one system may be selected for wider implementation across projects.
The selected developer will receive an incentive of INR 20 lakh upon successful completion and acceptance of the system. DMRC will also offer joint ownership of intellectual property, allowing the technology to be commercialised beyond metro projects through a revenue-sharing framework. The corporation will support development by providing domain expertise, access to historical project data and testing infrastructure, while the partner will contribute technical development and source code.
Proposals were invited through the government e-procurement platform, with submissions due in early March, while a pre-bid interaction was scheduled for mid-February to clarify technical and operational aspects of the project.
Source PTI
FAQ
Q1. What is the new AI initiative proposed by DMRC?
The Delhi Metro Rail Corporation (DMRC) plans to develop an AI-based project management system to improve the planning, monitoring and execution of metro infrastructure projects. Unlike conventional software that only tracks milestones, the proposed system will actively support decision-making by predicting delays, identifying risks early and suggesting corrective actions across different stages of project execution.
Q2. How will this AI-driven system work in practice?
The platform will rely on historical data from past metro projects to build more realistic schedules and risk models. It will dynamically adjust timelines based on site-level factors such as manpower availability, equipment performance and external disruptions. By continuously analysing live data, the system is expected to help project teams respond faster and minimise execution bottlenecks.
Q3. What additional monitoring and compliance features are planned?
Beyond scheduling, the AI system will monitor materials, machinery and labour usage in real time. Automated document analysis will flag missing approvals, incomplete inspections and potential regulatory gaps. DMRC also plans to use AI-enabled drones and cameras to compare on-ground progress with approved designs, strengthening site oversight and reducing manual checks.
Q4. How is DMRC involving startups in this initiative?
DMRC has invited startups to co-develop the platform through a collaborative model rather than a traditional tender. Development costs will be shared under a memorandum of understanding, with clearly defined responsibilities. Startups will be evaluated by an expert committee, and up to three may be shortlisted to develop and host the system on DMRC servers for six months.
Q5. What incentives are being offered to selected developers?
The developer whose system is finally selected will receive an incentive of INR 20 lakh upon successful completion and acceptance. In addition, DMRC will offer joint ownership of the intellectual property, allowing the solution to be commercialised beyond metro projects through a revenue-sharing arrangement, creating long-term value for both parties.
Q6. When is the system expected to be deployed?
Proposals were invited through the government e-procurement platform, with submissions due in early March and a pre-bid interaction held in mid-February. After development, testing and evaluation, the system is expected to be deployed in phases, with wider rollout planned based on performance and operational effectiveness.
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