Research built to be used, not just published.
Maitras.ai is an independent research and policy platform working at the intersection of tax data analytics, artificial intelligence in tax administration, and public finance systems for developing economies.
Leadership
Founder & Direction
Over 30+ years spanning Big 4 advisory, senior tax leadership in major mining and energy groups, and a decade embedded in a national tax administration, he has led the transformation of a revenue authority's compliance function from the ground up.
Direction
Sujoy Maitra works at the intersection of international taxation and applied data science — one of the few practitioners globally to have designed, built and deployed sovereign-level AI tax intelligence systems that are live inside a national revenue authority today. His career answers the question every Domestic Revenue Mobilisation (DRM) program eventually confronts: how does a developing country move from paper-based compliance to data-driven revenue administration, using country systems its own officers can run, defend and sustain?
Track record
Over 30+ years spanning Big 4 advisory, senior tax leadership in major mining and energy groups, and a decade embedded in a national tax administration, he has led the transformation of a revenue authority's compliance function from the ground up — contributing directly to measurable tax-to-GDP outcomes through improved audit selection, compliance risk management and revenue forecasting. His work has been carried out within a Medium-Term Revenue Strategy (MTRS) context and aligned with TADAT performance dimensions, including accuracy of reporting, effective risk management and timely dispute resolution.
Capacity building
Capacity building has been central, not incidental: he built the authority's first sovereign analytics capability, trained a multidisciplinary team of more than 80 officers in advanced audit, data analytics and AI tooling, and established transfer pricing audit capability from inception through to landmark settlements with multinational groups — institutional capability that operates independently of any single adviser.
Technical portfolio
His technical portfolio maps directly onto the digital compliance modernisation agenda of the international financial institutions: machine learning for risk-based audit selection, NLP and anomaly detection for fraud analytics, automated transfer pricing benchmarking for extractive sector transactions, real-time revenue forecasting for executive decision making, and explainable AI frameworks that keep every model output defensible before taxpayers, tribunals and oversight bodies. This includes integrating cross-border and third-party data — including Automatic Exchange of Information (AEOI) streams — into holistic taxpayer risk profiling, turning exchanged financial account data into actionable compliance intelligence. The architecture is deliberately replicable — designed for resource-constrained administrations across the Pacific, sub-Saharan Africa and South and Southeast Asia, and transferable through country systems rather than vendor dependency.
Taxation expertise
On the taxation side, his expertise covers extractive industry taxation and resource rent design, transfer pricing and BEPS implementation, AEOI and Common Reporting Standard (CRS) frameworks, exchange of information on request (EOIR), tax controversy and large taxpayer audit methodology — grounded in engagement with OECD technical working groups and multilateral reform programs.
Our Research Team
Maitras.ai draws on a network of contributing analysts, economists, and policy researchers whose combined careers span taxation, revenue analytics, and financial-crime detection.
Our contributors bring decades of combined practitioner experience across revenue administration, transfer pricing, and anti-money-laundering analytics — much of it earned inside working tax authorities and across cross-border jurisdictions rather than from the outside. That grounding is what lets our studies move past commentary and into the operational detail of how tax and financial-crime systems actually function.
Each published study is developed by the researchers best suited to it: economists who understand the fiscal mechanics, data analysts who can interrogate the numbers, and policy specialists who translate findings into terms that revenue authorities and finance ministries can act on. The team works under the research direction of the founder, with contributors engaged study by study according to the expertise each one calls for.
Economists
Fiscal mechanics, tax base analysis, and revenue modelling.
Data Analysts
Interrogating administrative data and building the underlying indices.
Policy Specialists
Translating findings into terms revenue authorities can act on.
Revenue Practitioners
Experience earned inside working tax authorities and cross-border audits.
Maitras.ai is an independent research and advisory platform focused on tax data analytics, AI in revenue administration, and the measurement of economic activity in developing economies.
We are independent of commercial and political sponsorship; our findings rest on published data and stated methodology, and our datasets and code are released for replication wherever agreements permit.
The record is usually there. What's missing is the work of making it legible — and holding it accountable to the people it describes.
Mission & Vision
Our Mission
To produce rigorous, independent research on tax systems, public finance, and economic inclusion — and to translate that research into tools that policymakers and administrations can actually put to use.
Our Vision
A future where fiscal systems in developing economies are transparent by default — where every citizen, and every institution meant to serve them, can see how public money moves.
Research Methodology
Name the Gap
Source the Evidence
Build the Index
Publish
Every study begins with a question about what the record leaves out. Before collecting data, we identify the specific gap to close: what is currently unmeasured, undercounted, or left undisclosed in a country's fiscal story.
From there, we compile evidence directly from primary government records, multilateral databases, and institutional sources, tracing every figure to its authenticated origin. When needed, we shape this data into reproducible, clearly weighted composite indices rather than one-off headline figures.
Every calculated figure is explicitly disclosed as such — the line between what was reported and what was derived is never blurred.
Before release, findings undergo rigorous internal review for consistency. We publish each study in two formats: a full academic version for peer scrutiny, and a concise, decision-ready brief tailored for policymakers.
Core Values
Accuracy First
Every figure is sourced, verified, and disclosed before it appears in a published study.
Independence
Our research is conducted without commercial or political sponsorship shaping its conclusions.
Transparency by Design
We disclose our methods and sources as thoroughly as the systems we ask others to disclose.
Usability
Research that isn't usable by the people it's about is, to us, unfinished.
Regional Grounding
We build from local context outward, not from global frameworks inward.
Long-Term Accountability
We revisit and update our own indices as new data becomes available, rather than treating publication as an endpoint.
Why Our Research Matters
In developing economies, the difference between a functioning tax system and a failing one often comes down to what the data can — and can't — show. Where revenue is hard to see, it is hard to collect, hard to trust, and hard to defend.
- → Revenue that isn't measured accurately is revenue that leaks — through under-assessment, evasion, and mispricing no one can quantify.
- → Tax systems that citizens can't see are tax systems they can't trust or hold accountable.
- → Cross-border profit shifting that isn't traced is a tax base that quietly erodes without a single visible transaction.
- → AI deployed in revenue administration without local context risks automating the same blind spots it was meant to remove.
Who We Serve
Tax Administrations
Revenue authorities looking to modernize collection and close informal-sector gaps.
Policymakers
Government offices needing decision-ready research on fiscal and gender policy.
Development Agencies
Multilateral and bilateral partners funding transparency and inclusion programs.
Researchers & Academics
Scholars building on our indices, datasets, and published methodologies.
Collaborations
Studies developed in partnership with institutions and organizations across the region.
Revenue authorities & ministries of finance
Regional banks & financial institutions
Multilateral & bilateral development partners
Universities & independent research bodies
Beyond our formal partners, we are always glad to lend our research to those who can put it to use — research scholars, companies, and universities are all welcome to reach out for access, collaboration, or guidance drawn from our work.
Join Our Research Community
Whether you're a researcher, an institution, or a reader who cares about fiscal transparency — there's a way to work with us.