Strategy. Scaling enterprise AI. Physical AI. Building products.

I set the vision for enterprise AI, and I stay until people actually use it.

I lead enterprise AI transformation and platform work at Deloitte Consulting. At a global logistics company I set the vision and strategy for the AI Foundations platform and lead the team building it: the cloud, data, agent and model layers underneath, and the experience layer where nearly half a million employees meet AI at work. CIOs, CTOs and Chief AI Officers bring me in to decide what to build, in what order, and how to know it is working.

Email me LinkedIn

Frisco, Texas. Open to the SF Bay Area and remote US.

The AI Foundations platform Four layers. One job: put AI in everyone's hands, safely.
  1. AI experience layer One front door for every employee, with context and personalization by role. Gemini Enterprise is one of the experiences behind it. Built for nearly half a million employees; Gemini Enterprise alone has tens of thousands live, scaling toward six figures
  2. Agent and model foundation Build, evaluate, release and watch agents and models. AgentOps and MLOps live here.
  3. Data foundation Governed data products so agents have inputs you can trust.
  4. Cloud foundation Landing zone, identity, networking and cost control everything else runs on.
Guardrailsbuilt with the security and governance teams, not bolted on after Adoptionmeasured and owned with the business, not left to a comms plan

Four regions. Part of the agentic AI program, worth tens of millions, that I won and lead.

AI and data revenue I have closed
$90M
Delivery program I led, 200+ engineers
$200M
Pipeline for Orion in 12 months, from nothing
$14M
Employees the AI front door is built for at a global logistics company
~500K
Weekly active usage reached in 90 days on a 25,000-license rollout
80%
Enterprise client executives I have pitched Orion to
70+
Google Cloud All-Star Partner of the Year, AI Innovation
2025

What I do

Four things I am good at. The rest I hire for.

Strategy

Advising executive teams on where to take the organization and how to structure it to get there: operating model, org design, cost, and the sequence of moves. I did this for a global consumer electronics company that wanted to transform its product organization, and showed its leadership a nine-figure saving over four years.

The product organization strategy

Scaling enterprise AI

Setting the vision for how a whole enterprise will use AI, then building the platform, the guardrails and the operating rhythm that make it real for tens of thousands of people. I measure the strategy on weekly active usage, not licenses sold.

The platform, the playbook, the migration

Physical AI

AI that looks at the real world and makes a call. I am building Deloitte's go-to-market for it: the offer, the pipeline, turning leads into signed work, and the delivery behind it. The market is early, and I would rather say so than dress it up.

Where I am taking it

Building products

Seeing the product before it exists, writing the thesis, and leading a team to build and sell it. I have done it with a multi-agent platform, a cloud analytics product and an NLP service.

Orion and the others

How I think about it

“Enterprise AI is no longer a model question. It is a leadership question. The organizations that win will be the ones with leaders accountable not just for the strategy, but for the adoption curve, the operating model, and the outcome.”

I have watched a lot of enterprise AI die between the pilot and the P&L. The technology usually works. What is missing is someone who treats adoption as their job, with the same rigor a sales leader brings to a forecast.

So I hold myself to both halves. I set the strategy with the executive team, and I own the number of people who used the thing this week. One without the other is not leadership.

The work

Vision, strategy, execution. Here is what that looked like.

Strategy

A product organization, restructured on paper first

Global consumer electronics company. Three-month strategy program for the executive team.

The vision
The leadership wanted to transform how the product organization worked and what it cost, without breaking the thing that made the products good. I framed it as an operating model question before an org chart question: decide how work should flow, then decide who sits where.
The strategy
A three-month program with the executive team: baseline the current organization and its cost, define the target operating model, design the structure to match it, and sequence the moves so the savings arrive without a dip in delivery.
The execution
A target operating model, an org design, and a four-year plan the executives could take to their board, with the savings quantified year by year. The total was a nine-figure saving over four years.
The executives
I worked directly with the product and technology leadership through the program, from the first baseline to the final recommendation, and the choices in the plan were theirs as much as mine.

Scaling enterprise AI

The AI Foundations platform

Global logistics company. Agentic AI program worth tens of millions, won and led.

The vision
A Fortune 100 company with an entitlement of nearly half a million seats and a lot of ambition. I made the case to its executives that the way to get value was not another set of pilots but one shared foundation every team could build on, with a single front door where AI meets each employee in the context of their role.
The strategy
Four layers, built in order: a cloud foundation, a data foundation, an agent and model foundation with AgentOps and MLOps designed in, and an AI experience layer on top, organized around personas so each of nearly half a million employees gets the company context and personalization their job needs. Guardrails were designed with the security and governance teams from the start, and adoption was given an owner on the business side.
The execution
I lead the team building it. Gemini Enterprise, one of the experiences behind the front door, has tens of thousands of people using it and is scaling toward six figures across four regions. I am accountable for the governance, the security and procurement path, the change management, and the usage curve.
The executives
I won the program on the strength of the adoption playbook below and advise the client's technology and business leadership on what to build next and how to judge whether it is working.

The adoption playbook

Fortune 100 client. A 25,000-license Gemini Enterprise rollout.

The vision
The contract is not the finish line. I set the goal as weekly active usage, with the executive sponsor, and treated adoption as a discipline with the same rigor a sales leader brings to a forecast.
The strategy
Role-based use cases, champions inside each business unit, usage measured weekly, and the operating model written down so the approach would work without me in the room.
The execution
From zero to 80% weekly active usage in 90 days. The playbook then became an enablement program: 10 to 15 Build-an-Agent workshops in nine months, 700+ Partners, Principals and Senior Managers trained, and the Canada and Japan member firms running it on their own.
The executives
The playbook won the program above, worth tens of millions, and was reused at an enterprise mobile-computing maker, a major US life insurer and other accounts. Deloitte was named Google Cloud All-Star Partner of the Year 2025 for AI Innovation on the back of this motion.

The 36-hour migration

Major bank in Australia. $40M AUD platform, 17+ engineering teams.

The vision
Replace a legacy document platform serving 40,000 bank users with a Documents-as-a-Service platform the bank could keep migrating other systems onto, and do it without taking the bank down for a weekend.
The strategy
A platform delivered across 17+ teams, with a roadmap for bringing further systems onto it, and a cutover plan rehearsed to the hour.
The execution
Response times 10.8 times faster than the system it replaced. We moved 40,000+ users in a 36-hour production cutover with no unplanned downtime. Customer satisfaction came in at 92.86% and usage rose by up to 28%.
The executives
I ran the program with the bank's leadership as the accountable lead and was promoted within six months. This is older work, and it is still the one I get asked about.

Physical AI

A go-to-market for a market that is just forming

Deloitte. Offer, pipeline, sales conversion and delivery for Physical AI.

The vision
The next wave of enterprise AI value is in systems that see and act in the physical world: warehouses, fleets, plants, field operations. Most clients are at their first proof of concept. The firms that shape how Physical AI is bought and deployed now will set the pattern for the next decade, and I want Deloitte to be one of them.
The strategy
Treat it like a product launch, not a research project. Define the offer in the language of operations leaders, pick the use cases that pay back inside a year, build pipeline on named accounts, and make the first deliveries the reference stories for the next ten.
The execution
I am building the offer, the pipeline, the lead-to-sale motion and the delivery capability, and working with clients on early proofs of concept such as computer vision at the edge for field operations.
Where it is
Early. I am not going to quote pipeline or production numbers for a market this young. What I will say is that it is the first work I have led where the AI has to be right about a physical place, not a document, and I find that a harder and more interesting problem.

Building products

Orion

Multi-agent platform for sourcing and procurement. Created from zero.

The vision
Sourcing and procurement run on judgment calls spread across dozens of people and systems. I saw that a set of specialized agents, orchestrated end to end, could carry most of that work with the compliance enforced by the system rather than by policy. The starting point was no product, no reference customers and no demand.
The strategy
I wrote the thesis, designed the architecture and wrote the pitch: 15+ specialized agents orchestrated end to end on Vertex AI, ADK Agents, Gemini 2.5, Cloud Run and BigQuery, sold as a Phase 0 engagement first so clients could see it work on their own data.
The execution
$14M in pipeline in twelve months. Three Phase 0 engagements closed, and the segment named me Product SME. Live at a large technology company and a major US telecom, with a 50% productivity gain, a 50% velocity gain and 100% system-enforced compliance.
The executives
I pitched Orion to 70+ enterprise client executives across the US, Canada, Latin America, the UK and the Middle East, briefed Deloitte's US Consulting CEO and 60+ senior leaders on the thesis behind it, and it became the reference for Deloitte's own agentic platform.

Also built

Earlier products, same approach.

  • A cloud data analytics platform worth tens of millions at a Tier-1 US life and retirement carrier. I set the product vision, strategy and roadmap, shipped AnnuitiesHQ and LifeIQ, and founded the release management function.
  • An NLP privacy-detection service for a global news and information company. Team of 15, from the first whiteboard to production, finding and classifying personal information in unstructured content.
  • HORSE, a grid-computing reporting engine for a global market research firm. 300,000 reports, run times cut by 20 times. It won the Tata Innovation Jury Award in 2006 and taught me that the unglamorous workload is usually the valuable one.

In the room with

The executives I advise, and what they ask me for.

What I bring to a leadership role

What a VP of AI has to carry, and where I have carried it.

Vision and strategy
I set the direction for how an enterprise will use AI and sequence it into a platform the whole company can build on: cloud, data, agents and models, and the experience layer, with AgentOps and MLOps designed in rather than added later.
Execution, measured
Rollouts at 25,000 licenses and at nearly half a million, judged on weekly active usage. If people are not using it, I do not count it.
Guardrails with the people who own them
Security, governance, procurement and legal run alongside every deployment I lead. I would rather spend the first month with the CISO's team than the last month explaining to them.
Big programs
A $200M multi-year delivery program with 200+ engineers across the US, India and Europe, and more than twenty years of large platform launches and migrations behind it.
Revenue and partners
$90M in AI and data revenue closed. As the go-to-market lead for Deloitte's Google Cloud alliance I set account strategy and worked pursuits with quota-carrying sellers through forecast, deal inspection and close.
Trusted in the executive room
I architected Orion myself and I am 5x AWS certified, so when I sit with a CIO or Chief AI Officer I can draw the agent architecture and the business case on the same whiteboard. That is why they keep me in the room.

Talks and recognition

Where the work has been put on a stage.

Career

Twenty-plus years, four countries, and one way of working: set the direction, build the platform, own the result.

  1. 2021 to present

    Deloitte Consulting

    Enterprise AI Transformation and Platform Leader, AI and Engineering (Associate Vice President)

    Set the vision and strategy for the AI Foundations platform and lead the agentic AI program, worth tens of millions, at a global logistics company. Go-to-market lead for the Google Cloud alliance. Trusted advisor to CIOs, CTOs and Chief AI Officers; led a three-month product organization strategy for a global consumer electronics company. Clients have included a global technology company, a global news and information company, a major US telecom, a leading fintech software company, an enterprise mobile-computing maker and a major US life insurer. Created Orion and the enterprise AI adoption playbook.

  2. 2015 to 2021

    Lincoln Financial Group

    Senior Product Manager, Cloud and Data Analytics

    Set the product vision, strategy and roadmap for a cloud data analytics platform worth tens of millions at a Tier-1 life, annuities and retirement carrier. Established product and release management discipline in a regulated environment.

  3. Earlier career

    Tata Consultancy Services

    Technical Program Manager and Engineering Leader, India, US and Australia

    A major bank in Australia, Australia's largest retailer, a global market research firm and India's central bank. The 36-hour migration of 40,000 users, and a grid-computing engine that cut 300,000 report run times by 20 times.

Education and certifications

Anna University, Chennai

Bachelor of Technology, Information Technology

Bachelor of Engineering, Civil Engineering

Certifications

5x AWS Certified (Solutions Architect, SysOps, Developer Associate)

PMP, Certified Scrum Master, PRINCE2 Practitioner, ISTQB Certified Tester