11+ years leading GenAI, ML, customer intelligence, and cloud-data programs across insurance, life sciences, and retail. I help enterprises move AI beyond demos — into governed, audited production with clear ownership and measurable outcomes.
I don't do demos.
I ship outcomes.
Different industries, different scales. Same delivery pattern: stuck POCs → governed production.
Own delivery governance for a ~$5M Data & AI portfolio across Gulf insurance operations — propensity-led customer intelligence, GenAI cross-sell, and a customer data platform spanning 15+ insurance products across Turkey and Lebanon.
Delivered key workstreams within pricing analytics modernization across 14,000+ retail stores in Europe and North America — 100TB+ Azure migration, scalable analytics workflows, feature pipelines, and downstream BI enablement.
Delivered ML compliance analytics across 12 APAC countries — improved precision from ~70% to ~95%.
Led delivery of 500TB+ AWS Redshift migration for a financial-services client — ~$280K annual savings.
Built experimental agentic workflows for job intelligence, profile matching, and outreach automation — exploring multi-agent orchestration and AI-assisted decisioning patterns relevant to enterprise GenAI delivery.
Built an AML detection model surfacing high-risk entities. Industrialised Power BI reporting for 200+ users with ~80% cycle-time reduction.
Six dimensions of capability ownership — from business problem to governed adoption.
Convert ambiguous business needs into AI/ML use cases, success metrics, roadmap, and delivery scope.
Drive data profiling, DQ validation, source alignment, entity resolution, and business rule clarification.
Shape AI/ML, GenAI, RAG, and cloud-data architecture with technical teams. Challenge unrealistic expectations early.
Sprint governance, RAID logs, steering reviews, executive reporting, vendor coordination, escalation discipline.
Responsible AI, model governance, audit documentation, human-in-the-loop review, production safeguards.
Track ROI, conversion, retention, cost savings, productivity, business adoption, and platform usage.
Six recurring capability programs — each mapping to real outcomes in the work above.
Move GenAI & ML out of demos into governed production with monitoring, rollback, cost controls, drift detection, HITL gates.
Migrate legacy analytics to Azure / AWS / Databricks / Snowflake — readying them for AI/ML workloads at 100TB+ and 500TB+ scale.
Embed LLMs, RAG, vector search, and agentic workflows into existing enterprise systems with prompt controls and audit logging.
Establish Responsible AI controls, model risk frameworks, audit-ready documentation, LLMOps standards, and AI/ML Centre of Practice.
Build CDPs, propensity / churn / cross-sell / win-back models, and customer 360 capabilities integrated into business workflows.
Define delivery frameworks, governance structures, team operating models, vendor strategies, and value-tracking systems.
Tools as means, not identity. Leadership-led at the top of the stack.
Enough technical depth to lead the right solution, challenge bullshit, and govern delivery. Not the person writing the model — the person making sure the right model gets shipped.
Recurring patterns in steering committees and program reviews.
Known for converting ambiguous AI asks into structured roadmaps, ownership models, and executive-ready updates that hold up in steering reviews.
Brings structure around data readiness, model risk, Responsible AI, documentation, and production controls — making AI programs defensible to audit and risk teams.
Strong at bridging business sponsors, technical teams, and governance stakeholders to keep AI programs moving from POC into production adoption.
Published thinking on AI delivery, governance, and architecture.
Long-form essays on POC-to-production, GenAI governance, and demo-stage failure modes are in progress. Published pieces will land here.
I work with enterprises that need business-facing AI leadership, delivery governance, technical fluency, and production adoption — not slideware.
Active across India, Gulf, Europe, and global capability centres.
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