NowLeading a ~$5M Data & AI portfolio · Gulf insurance

I take AI from POC → to P&L.

11+ years leading GenAI, ML, customer intelligence and cloud-data programs across insurance, life sciences and retail. I move AI beyond demos into governed, audited production with clear ownership and measurable outcomes.

agents.live● live
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Portrait of Suman Mukherjee
hi, I'm Suman 👋
0+
Years in AI & data
$0M
Portfolio owned
~0%
Lead conversion lift
0TB
Cloud migrated
01 / Selected work

Shipped at enterprise scale

Different industries, different scales. Same delivery pattern: stuck POCs become governed production.

Insurance · Gulf · 2024–now

Enterprise AI Transformation

Own delivery governance for a ~$5M Data & AI portfolio across Gulf insurance: propensity-led customer intelligence, GenAI cross-sell, and a customer data platform spanning 15+ insurance products across Turkey and Lebanon.

Azure MLDatabricksGenAICDP20+ team
~30%
Retail · Global

Pricing Analytics Modernization

Workstreams across 14,000+ stores in Europe and North America, incl. a 100TB+ Azure migration.

SynapseADLS
14K
Medtech · APAC

Compliance ML Capability

ML compliance analytics across 12 APAC countries. Precision from ~70% to ~95%.

PythonAnomaly
95%
Financial services

500TB+ AWS Migration

Led delivery of a Redshift migration with ~$280K annual savings.

RedshiftGlue
$280K
Insurance · Earlier

AML Detection & Reporting

AML model surfacing high-risk entities, plus Power BI for 200+ users with ~80% cycle-time cut.

DatabricksPower BI
80%
Personal lab · 2025

AI Experiments & Product Thinking

Experimental agentic workflows for job intelligence, profile matching and outreach automation, exploring multi-agent orchestration and AI-assisted decisioning patterns for enterprise GenAI delivery.

n8nOpenRouterApifyMCP
Labs
02 / Agent Lab

How I ship agents safely

Pick a scenario and run it. Every step is logged, checked against guardrails, and a human signs off before anything reaches production.

Human-in-the-loop gate.

audit.logidle
0Agent steps
0Guardrails
—Human call
Illustrative simulation. No client data, no live model calls.
03 / Watch list

Agentic AI in five talks

What I point teams to when they move from chatbots to agents: what works, what breaks, and how multi-agent systems ship in production.

Videos load from YouTube (privacy-enhanced mode) only after you press play.

I don't do demos. I ship outcomes, with governance that holds up in the audit room.

04 / How I lead

What I own

Six dimensions of ownership across AI programs, from business problem to governed adoption.

01

Business problem framing

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Convert ambiguous business needs into AI/ML use cases, success metrics, roadmap and delivery scope.
02

Data readiness

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Drive data profiling, DQ validation, source alignment, entity resolution and business rule clarification.
03

Solution direction

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Shape AI/ML, GenAI, RAG, agentic and cloud-data architecture with technical teams. Challenge unrealistic expectations early.
04

Delivery governance

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Sprint governance, RAID logs, steering reviews, executive reporting, vendor coordination and escalation discipline.
05

Risk & controls

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Responsible AI, model governance, audit documentation, human-in-the-loop review and production safeguards.
06

Adoption & value

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Track ROI, conversion, retention, cost savings, productivity, business adoption and platform usage.
05 / Technical fluency

Top of the stack

Enough depth to pick the right solution, challenge weak claims and govern delivery. I don't write the model; I make sure the right one ships.

L00 · EXPLORING NOWAgentic & GenAI frontier

LangGraphCrewAIClaude Agent SDKOpenAI Agents SDKMCPA2A protocolLLM evalsHugging FaceOllamaQdrant

L01 · TOPAI strategy & delivery

AI roadmapsUse-case prioritizationDelivery governanceExec reportingOperating models

L02Governance & risk

Responsible AILLMOpsModel riskAudit docsHuman-in-the-loopData privacy

L03AI / ML solutions

Azure OpenAIAWS BedrockLangChainRAGVector searchAgentic AIPropensity models

L04Cloud & platform

Azure MLDatabricksSynapseAWS RedshiftSnowflakeMLflow

L05 · BASEEngineering & BI

PythonSQLPySparkPower BITableaun8n

L00 is what I'm building hands-on labs and POCs with right now; L01 to L05 is what I lead in client delivery.

06 / Let's talk

Build something real

For enterprises that need business-facing AI leadership, delivery governance and production adoption, not slideware.

Direct line

24-hour response, straight from my inbox. No assistant, no funnel. Active across India, the Gulf, Europe and global capability centres.

Email me → LinkedIn ↗