Every consultancy is selling AI adoption. I do the opposite. I help enterprises build the governance, reliability, and compliance infrastructure that makes AI deployments survive contact with regulators, auditors, and production.
Priority banking, wealth management, commercial lending, cross-border strategy — I've done the work. When I design an AI governance framework, it's informed by years of managing portfolios, handling compliance audits, and operating under regulatory pressure. Not by reading about them.
I'm actively building AI trust infrastructure — agent registries, reasoning capture, reliability monitoring. My recommendations come from production, not decks. When I tell you something works, it's because I've shipped it.
RBI's risk weight guidelines, SEBI's advisory frameworks, IRDAI's automation rules, and the DPDP Act are converging on AI simultaneously. I've worked under each regulator operationally — not just studied them for a client engagement. That changes what you recommend.
Everyone else sells AI acceleration. I help you build the trust layer that lets you scale without regulatory exposure. The enterprises that govern their AI now — agent registries, audit trails, bounded autonomy — will have a structural advantage when enforcement arrives.
India Stack (UPI, Account Aggregator, GST), GIFT City IFSC, India-ASEAN corridors — I've operated across these systems, not observed them. Expansion across Singapore, Thailand, Vietnam, Indonesia, and Malaysia. $450M capital deployed, regulatory licensing across five jurisdictions.
Credit risk architecture. Portfolio construction. HNI relationship management. Campaign analytics. Basel III compliance. I understand the business the AI is supposed to serve — which means I know which problems are worth solving with AI and which aren't.
Agent registry design, reasoning capture architecture, bounded autonomy frameworks, and policy enforcement layers. For enterprises that need to know what their AI is doing, why, and within what limits.
Mapping AI decision-making to RBI, SEBI, IRDAI, and DPDP Act requirements. Audit trail architecture, explainability reporting, and cross-regulation conflict resolution. Built for India's multi-regulator reality.
Drift detection, hallucination monitoring, fairness evaluation, and model governance frameworks. Designed for Indian data patterns — seasonal cycles, regulatory events, and market-specific distributions.
For leadership teams making build-vs-buy decisions, defining AI roadmaps, or evaluating vendor risk. I bring 12 years of financial services operations to the strategic layer — not just the technology.
Continuous assessment frameworks built on India Stack data flows — UPI, Account Aggregator, GST. Risk architecture designed around new data, not legacy models with new inputs.
Regulatory licensing, corporate structuring, and market strategy across India and ASEAN. Experience across 5 Southeast Asian jurisdictions and India's GIFT City IFSC framework.
Ongoing advisory relationship for leadership teams navigating AI governance, regulatory strategy, or market entry. Typically retained quarterly.
Enterprise-wide AI audit — agent inventory, governance gaps, regulatory exposure, and a prioritized implementation roadmap. 4-6 week engagement.
Hands-on architecture and technical oversight for AI governance infrastructure, risk systems, or compliance layers. Embedded with your team.
If you're deploying AI at scale and need someone who's built governance infrastructure from the inside — not someone who's read about it — let's talk.