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About

Building the datasets the world is missing

We build novel datasets and economic intelligence from unstructured data using frontier AI.

Our Team

Dr. Peter Lambert, Director and Co-Founder

Dr. Peter Lambert

Director and Co-Founder

University of WarwickLondon School of EconomicsCentre for Economic Performance (CEP)Centre for Macroeconomics (CfM)CAGE Research Centre

Peter is an economist studying organisations, industries, jobs, and economic growth. His research leverages large novel datasets — text, transactions, networks, images — and frontier AI tools to study behaviour within and across organisations. He holds a PhD in Economics from the London School of Economics.

Selected Research

  • AI-Generated Production Networks: Measurement and Applications to Global Trade (2024)
  • Remote Work across Jobs, Companies, and Space (NBER, 2023) — Best Paper Award, CESifo
  • Bad Bank, Bad Luck? Evidence from 1 Million Firm-Bank Relationships (2024)
  • Anatomy of Automation: CNC Machines and Industrial Robots in UK Manufacturing (2025)

Selected Presentations

  • Google DeepMind AI for Social Science Event — keynote on AI/LLMs for economics research
  • EUR-CEPR Workshop: Trade, Geography, and Industrial Organisation
Dr. Yannick Schindler, Co-Founder

Dr. Yannick Schindler

Co-Founder

London School of EconomicsCentre for Macroeconomics (CfM)

Yannick is a macroeconomist whose research spans technological change, health economics, and financial markets. He deploys Big Data and AI tools to build novel measurements of the economy from administrative and archival sources. He holds a PhD in Economics from the London School of Economics and previously held positions at Princeton University and the European Central Bank.

Selected Research

  • Machinery of Progress: Charting the Capabilities of Capital Equipment, 1998–2023 (2025)
  • Bad Bank, Bad Luck? Evidence from 1 Million Firm-Lender Relationships (2024)
  • The Macroeconomic Impact of Chronic Illness in the UK — Journal of the Economics of Ageing (2025)
  • Prosperity Through Health — policy paper with Sir John Bell and Andrew Scott (2024)

Selected Presentations

  • FDIC, Federal Reserve Bank of Boston, Downing Street Data Science Unit
  • Stockholm School of Economics, EEA Congress, HM Treasury
500M+
Records Processed
4
Flagship Data Products
5+
Countries Covered
LSE
Founded at

Our Story

Applied Economics AI was founded in 2022 by economists at the London School of Economics who saw that the digital age was generating vast quantities of data — but the majority of it was trapped in unstructured formats. Financial documents, job postings, administrative archives, clinical observations. Rich in information, but inaccessible to traditional economic analysis.

We built the tools to change that. Using frontier AI — large language models, natural language processing, and agentic AI pipelines — we extract structured, analysis-ready data from sources that were previously impossible to work with at scale. What began as a research lab at the LSE Centre for Economic Performance has grown into a consulting and data business serving governments, central banks, statistical agencies, and institutional investors.

Our Mission

We harness cutting-edge AI to unlock the wealth of information trapped in unstructured data sources, transforming raw information into actionable knowledge for academic research, policy analysis, and commercial decision-making.

Our work sits at the intersection of academic economics and commercial AI — too rigorous for most consultancies, too practical for most academic groups, and too bespoke for standard data vendors. We bring deep economic expertise to real-world problems, and frontier AI methods to serious economic questions.

Get in touch

Tell us about your challenge. We'll outline how our team, methods, and data can help.