Sunil Mathew Fractional CAIO
00 An embedded AI executive — part-time, accountable for outcomes · India

From pilot purgatory to governed production.

I own your AI strategy, governance, and roadmap, get your first use cases into production, and leave your team able to run it — without the cost or wait of a full-time Chief AI Officer.

Book a discovery call → Start with an AI Readiness Assessment

26 years at Google · Amazon · Walmart — and building agentic AI now.

Sunil Mathew
Sunil MathewFractional CAIO · ex-Google, Amazon, Walmart
26 years, shipped at
01 The leadership gap

You don't have an AI tooling problem. You have an AI ownership problem.

The signs are familiar. Pilots that demo well and never ship. AI tools spreading through teams with no one watching the data or the risk. A CTO already at capacity, now expected to add AI strategy on top. Your best engineers quietly leaving because nothing they build on actually reaches customers. And a board asking where the return is.

None of this is solved by another platform subscription. It's solved by one senior person holding the mandate — owning the strategy, the governance, the build-vs-buy calls, and the accountability for getting something real into production.

That's the seat I fill.

02 What a fractional CAIO owns

The whole AI agenda — not a corner of it.

// strategy

Strategy & roadmap

Your AI use cases sequenced by impact and readiness, aligned to where the business actually makes money.

// governance

Governance & risk

A governance model that turns shadow AI into sanctioned AI — mapped to the DPDP Act and your regulator (IRDAI, RBI, SEBI), and to global frameworks where you operate across borders.

// decisions

Build-vs-buy & vendors

The decisions that are expensive to reverse, made deliberately and defended.

// delivery

First use cases into production

Not more pilots. Two to three that ship, with evals and cost you can stand behind.

// board

Board & leadership reporting

Translating AI from anxiety into a plan your board can fund and track.

// handover

Capability transfer

Building the operating model and the literacy so your team carries it after I step back.

A consultant hands you a deck and leaves. I join the operating rhythm — and I'm accountable for whether the metric moves.
03 Where the lines are

Clear decision rights, from day one.

vs your CTO

Your CTO runs the engineering organisation. I own AI strategy and governance across the business and sit above delivery. We define decision rights at the start; I make the CTO's life easier, not harder.

vs a full-time CAIO

Same accountability and board-facing ownership, a fraction of the time and cost — and an engagement designed to phase out, not to become a permanent dependency.

vs an AI agency

They execute scopes. I own outcomes — and I'll tell you when the answer is don't build this.

04 The maker

I've shipped this at the scale where mistakes are expensive — and I'm in the trenches now.

26+
Years building software
3
Fortune-100s · Google, Amazon, Walmart
100M+
Users served by systems built
150
Engineers led across geographies
Sunil Mathew
Sunil Mathew · Bengaluru, India

I'm Sunil Mathew. Twenty-six years building and leading engineering at three Fortune-100s — Google, Amazon, and Walmart — on systems serving up to 100M+ users, leading teams of up to 150 across the US, UK, China, and India.

At Google I shipped a Generative-AI product and ran a platform at ~31 billion executions a week. At Amazon I re-architected Prime's membership core. At Walmart I modernised 300+ products from legacy into microservices and stood up AI and data-science capability. Today I lead agentic-AI work — multi-agent orchestration, RAG, evals, LLM-Ops — and I'm building an agentic-AI product of my own, so my judgment is current, not a memory.

"The rare part for this role: I've done both the executive strategy and the production delivery — and I teach this craft to senior engineers, so transferring capability to your team isn't an afterthought. It's how I work."

See how I teach the craft — The Living Craft →

— Sunil Mathew
05 The engagement

A 90-day spine, then we go where the agenda goes.

Phase 1Weeks 1–4

Assess

Readiness, roadmap, governance foundation. If we've already done the AI Readiness Assessment, we start here with a head start — and the assessment fee is credited.

Phase 2Months 2–3

Operationalise

Governance live, vendors decided, first use cases moving into production with evals in place.

Phase 3Ongoing

Enable

Capability transfer, operating-model documentation, and a clear path to either a leaner advisory cadence or your own full-time hire when scope justifies it.

Most engagements run 6–18 months — two to three days a week early on, tapering as your team takes the wheel.

06 Ways to work together

Three ways in.

Advisory
~2 days / month

Board cadence, governance oversight, and decision support for a team that's already moving.

From ₹1,50,000/ month
Enquire →
Most common
Embedded
~1 day / week

Roadmap ownership plus getting your first use cases into production.

From ₹3,50,000/ month
Enquire →
Transformation
2–3 days / week

Full ownership: build the function, the governance, and the team from the ground up.

From ₹6,00,000/ month
Enquire →

90-day minimum. Payment plans available. Most engagements begin with an AI Readiness Assessment.

07 The first step

Start with a diagnosis, not a contract.

The cleanest way in is the AI Readiness Assessment — two to three weeks, a fixed fee, and a board-ready roadmap you own regardless of what you do next. If you bring me on to drive it, the fee is credited toward your first month.

Prefer email? Write to me directly →

You don't need a $400K hire to get serious about AI. You need someone who's done it to own it for a while — and then hand it back.