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LTIMindtree secures Rs 3,000 cr AI mandate to power India’s next-gen tax intelligence system
The seven-year mandate, titled Insight 2.0, is designed to modernise the tax department’s analytics capabilities by integrating AI-powered tools that can deliver real-time, actionable insights to policymakers.
LTIMindtree said the contract underscores its growing role in large-scale public sector digital transformation initiatives, particularly in deploying AI and analytics at a national level.
LTIMindtree has secured a Rs 3,000 crore contract from the Central Board of Direct Taxes (CBDT) to build an artificial intelligence–driven programme aimed at overhauling India’s national tax analytics platform, marking one of the government’s largest technology investments in data-led policymaking, PTI reported.
As per the media report, the seven-year mandate, titled Insight 2.0, is designed to modernise the tax department’s analytics capabilities by integrating AI-powered tools that can deliver real-time, actionable insights to policymakers. The platform is expected to strengthen data-driven decision-making, improve compliance monitoring, and enhance the overall efficiency of tax administration.
According to the company, the project will focus on leveraging advanced analytics and machine learning to process large volumes of tax data, enabling faster detection of trends, anomalies, and potential risks within the system. By shifting from retrospective analysis to near real-time intelligence, the platform aims to support more responsive and targeted policy interventions.
Reportedly, LTIMindtree said the contract underscores its growing role in large-scale public sector digital transformation initiatives, particularly in deploying AI and analytics at a national level. The company has been expanding its footprint across government and enterprise digital programmes as India accelerates its push towards technology-led governance.
The CBDT-led initiative aligns with the broader vision of using emerging technologies to modernise tax administration, improve transparency, and support evidence-based fiscal policymaking in one of the world’s largest and most complex tax ecosystems.
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