Economist, engineer, and AI architect based in Vancouver — with two decades of work spanning evidence-driven AI, global institutions, and entrepreneurial ventures across three continents.
Available — advisory
Abhay's defining thread across two decades has been a refusal of the easy version. AI grounded in empirical evidence rather than self-reported metrics. Inference chains that are traceable, not opaque. Outputs that are measurable, not vibes-based. Decisions that are auditable — because in government, mission-critical, and industrial deployments, accountability is non-negotiable.
He holds a PhD in Economics from the University of British Columbia, a B.Tech in Chemical Engineering from IIT Kanpur, an MA in Economics from Lakehead University, and executive certificates from Harvard Kennedy School and Columbia Business School. The breadth isn't an accident — it's a method.
That same temperament — observable over performative, measurable over mystical, patient over hype-driven — runs through every page of the You 2.0 series. The series is, in many ways, what happens when an evidence-driven economist turns the same instruments on the question of how to actually live a life.
The work has always been the same: build systems where every inference is traceable, every output is measurable, and every claim survives a stranger's scrutiny.
The work spans surfaces that rarely sit on the same résumé — and that's precisely where the leverage is.
Action → activity → output → outcome modeling. AI systems built so that every inference is traceable back to observed reality. Used at scale in enterprise platforms processing 100M+ organizational documents.
Document intelligence, named-entity recognition, embeddings at scale. The architectural work behind production AI at organizations where precision and auditability are non-negotiable.
Panel data, impact evaluation, forecasting, actuarial modeling. Including a $500B pension system model covering 30M+ Canadian citizens and IFRS/GAAP-embedded indicators from OECD intangibles work.
Earth-observation, sensor fusion, industrial AI. Leadership of the EO-AI Labs at STAr IITK and applied research bridging satellite intelligence with on-ground decision systems.
0→1 product, enterprise scaling, acquisition exits. Three ventures founded — Lunge AI (acquired 2025), Moonshot Zero, and PPO-99 Capital — alongside advisory work for IIT Kanpur, Airawat AI, and standards bodies.
International recognition for evidence-based prediction methodology — the kind of work where claims have to survive adversarial evaluation.
Recognized work for the Bill & Melinda Gates Foundation on global development impact — methodologically rigorous, practically deployable.
OECD intangible-asset indicators, originally developed in his earlier research, are now embedded in global accounting standards. Scaffolding nobody sees, holding things up.
Each venture is an applied test of the same idea: build evidence-driven systems for the surfaces where it matters most.
Enterprise AI platform processing 100M+ organizational documents. Founded, scaled, and exited via acquisition in 2025.
lungesystems.com →The next venture — applied evidence-driven AI for mission-critical surfaces where the cost of being wrong is high and accountability is mandatory.
moonshotzero.com →An investment vehicle built around the same principles: durable signal over momentary noise, observable performance over self-reported narrative.
ppo99.com →Reader notes, advisory inquiries, speaking requests, or just to say hello.
Two decades of evidence-driven thinking, distilled into ten short books. Pick the area that's loudest for you right now — the series will meet you there.