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Dr. Kamini Garg · Fractional Head of Data & AI · Zurich

Most organisations are investing in data and AI.
Very few can point to the return.

That gap is what I close. I work as a Fractional Head of Data & AI with founder-led and growth-stage companies, taking the work through to production and connecting it to a decision the business can actually make.

A decade building models, pipelines, and data products across Swiss telco, global consumer health, and Fortune 500 supply chain. PhD in Informatics, USI Lugano.

Retention programmes across 1M+ customers  ·  demand forecasting across 11 EMEA markets  ·  forecast accuracy improved across thousands of SKUs

The technical work was hands-on. The question behind it was always about business outcomes.

The Gap I Close

Data investment without commercial return is just cost.

Most organisations have a data team doing serious work. Dashboards exist. Models get built. But when the board asks what changed commercially last quarter, nobody has a clean answer.

The cause is rarely technical. A model that never reaches production. A pipeline the commercial team does not trust. An AI feature that demos well and never ships. In each case the work exists. The outcome does not.

That last stretch is where I work. I own it end to end, from the priorities through to production and the decision it is meant to change.

Client Results

What the work looks like from the other side.

From founders and leaders who engaged Visthena directly.

“

We had data spread across many sources with no single source of truth, no clarity on what was really happening, and it was costing us time. Kamini brought it together and showed us where it was inflated or missing, gaps we only understood once she presented them clearly. Suddenly the gaps, and the actions to close them, were clear to us as founders and to our engineering team, and our next steps became far easier. We now understand our data, fix the gaps, and visualise it to make informed decisions, and for a lean team the daily alerts save us real time. Structured, efficient and thorough throughout. We would highly recommend Visthena.

Gayatri & Sanjana
Co-founders, Miyara Health
“

As our Fractional Head of AI, Kamini and Visthena have been central to WTW's progress, from getting our AI features ready for beta testing to now shaping the next phase of the product. She brings genuine technical depth, delivers reliably, and is someone I can count on to think through the hard problems with me. On top of that, she is a pleasure to work with. I would recommend Kamini and Visthena to any founder building an AI product.

Monika Müller
Founder, WTW
How I Engage

Three ways to engage

01
Fractional Head of Data & AI
Ongoing · 1–2 Days/Week · Core Engagement
Working alongside your leadership team on the data and AI roadmap, keeping it honest and connected to decisions that move the business forward.
02
Focused Delivery
Fixed Timeframe · Fixed Scope · Single Initiative
Hands-on delivery of one well-defined initiative, from an AI feature that needs to reach production to a data product the business is waiting on. What success looks like is agreed before the work starts, not after it finishes.
03
Data ROI Audit
3–4 Weeks · Fixed Fee · Fixed Scope
A structured diagnostic that gives you a clearer picture of where data investment is working and where it is not, with prioritised next steps attached to each finding.
Where It Usually Starts

The conversation usually starts in one of these three places.

Founder-led and growth-stage companies  ·  Switzerland, Germany, Austria

The data investment is real. The return is harder to see.

The work is happening. Dashboards exist, models have been built, the team is busy. But when the board asks what it has actually changed, what decision was made differently or what revenue moved, the answer is not there.

Nobody owns the data and AI decisions.

Perhaps that hire has not been made yet, or the person who held it has moved on. Either way nobody is accountable for turning the work into commercial outcomes, and that gap tends to cost more the longer it stays open.

Something specific needs to be built, and built properly.

An AI feature that needs to reach production, a model, a data product the business is waiting on. Something that matters enough that getting the framing wrong at the start would cost more to fix than the build itself.

From the Work

One example from the work that shaped how I approach every engagement.

A B2C telco was carrying operational cost from customers on legacy products. The right offers existed. The challenge was identifying which customers to move, when, and with what.

As analytics lead, I worked across commercial, product, and operations to build a targeting and offer-matching model. The approach was deliberate: test on a defined segment, validate the outcome, then scale.

I presented the results to the CMO and made the case for scaling. The go-ahead followed. The outcome was measurable yearly revenue growth and reduced operational cost through targeted customer migration.

Sector
B2C Telco
My Role
Analytics Lead, cross-functional
Approach
Test, validate, scale to CMO sign-off
Outcome
Revenue growth and cost reduction from targeted customer migration
Recent Thinking

How I think about this work

I write regularly about data and AI leadership, and about why so much of this work stalls in the gap between a technical result and a commercial one.

Read on LinkedIn →

If your data investments are not generating a return you can point to, that is a useful conversation to have.

If the timing is right, I would be glad to talk.

Kamini Garg

The person behind Visthena.

A decade of delivering measurable commercial outcomes from data and AI, across Swiss telco, global consumer health, and Fortune 500 supply chain environments.

Dr. Kamini Garg — Fractional Head of Data & AI, Zurich
My Story

Across every role I held before founding Visthena, the same moment came around eventually. At year-end leadership reviews, someone would ask what the data function had actually delivered that year. The honest answer was harder to give than it should have been. The technical results were real. The business results were unquantified.

This was not a capability problem. The teams were strong, the work was serious, and the investment was real. The missing piece was always the same. Nobody had agreed, at the start, what the work was actually supposed to change. So when the question came, the answer was not there.

That is what Visthena is for.

Since founding it, I have worked as Fractional Head of AI to a founder-led product team, taking AI features from prototype through to beta and into the next phase of the roadmap. I have also worked with a lean health startup whose data was spread across too many sources to trust, consolidating it into something the founders and their engineers could actually make decisions from.

The work before Visthena is what made that possible.

At Johnson & Johnson and Kenvue, I was the forecasting lead for demand sensing solutions across 11 EMEA markets, contributing to double-digit improvements in forecast accuracy across thousands of SKUs.

At Sunrise Communications, I was lead data scientist in the commercial function, leading a B2C migration strategy that grew revenue and running the B2B analytics function as Product Owner.

At UPC Switzerland, I built churn and propensity models that reduced retention costs across a customer base of over one million.

I hold a PhD in Informatics from the University of Lugano (USI) and have completed leadership development programmes at IMD Lausanne and SGMI St. Gallen.

Track Record

  • Demand forecasting at EMEA scale
  • Customer retention & churn modelling
  • Revenue optimisation, B2B and B2C
  • Operational efficiency & cost reduction

Experience

  • Visthena GmbH Founder & Fractional Head of Data & AI
  • J&J / Kenvue Senior Data Scientist, Supply Chain
  • Sunrise Lead Data Scientist
  • UPC Switzerland Data Scientist

Education

  • PhD, Informatics USI Lugano

Specialisms

  • Fractional Data & AI Leadership
  • AI Product Development
  • Customer Retention & Churn Reduction
  • Commercial Impact Measurement
  • Demand Forecasting & Supply Chain ROI

If something here resonates, I would be glad to talk.

The first conversation is short, with no agenda and no pitch.

Services

Three ways to work together.

Data and AI leadership, sized to what you actually need. Every engagement starts with a commercial question, not a technical one.

01

Fractional Head of Data & AI

Ongoing Retainer · 1–2 Days/Week · Strategic Leadership

My core engagement. I work alongside your leadership team as a part-time Head of Data & AI. For some companies that means owning an AI product through to production. For others it means being the person who keeps connecting existing data work back to what the business is actually trying to decide.

Whether the work involves a data pipeline, a predictive model, or an AI capability the business is considering — the business question always comes first.

  • Review the current data roadmap and align priorities to business goals
  • Support and unblock the data team, hands-on where it is useful
  • Evaluate AI and analytics opportunities against business return, not just technical feasibility
  • Represent the data function at leadership level, translating work into language the business can act on
  • Build internal capability so the work outlasts the engagement

Well suited to organisations with a data team in place that want senior perspective without a full-time hire. Structured around a defined number of days per month, with scope and terms agreed at the start.

How this works
1. First conversation A short call to understand current priorities, where the data investment is focused, and what the leadership team most needs to change. 2. Agree the scope Define the days per month, the focus areas, and what a useful first 90 days looks like. 3. Start work Embedded alongside the team, attending the right meetings, asking the right questions from day one. 4. Review regularly Monthly check-in on whether the engagement is delivering what the business needs, and adjust if not.
02

Focused Delivery

Fixed Timeframe · Fixed Scope · Single Priority Initiative

For organisations with a specific initiative they want built and delivered to a clear deadline. We agree on what success looks like before work begins. Delivery is structured around that outcome, not just getting the code shipped.

  • Agreeing upfront what decision or business outcome the work should enable
  • Hands-on delivery across data, modelling, pipeline, and production deployment
  • Technical execution handled end to end, from data to deployed solution
  • Stakeholder communication and progress reporting throughout
  • Knowledge transfer so the team can maintain and extend what was built

Suits organisations that have a clear initiative in mind and want the business framing built in from the start. Priced on a fixed scope and fixed fee basis, agreed before work begins. The fee depends on the initiative and is discussed once the scope is defined.

How this works
1. Define the question What business outcome will this initiative enable? 2. Set the metric What does success look like in P&L terms, and how will we measure it? 3. Deliver and measure Hands-on delivery tied to the agreed outcome. 4. Review and close What the work delivered against what was agreed, and what to adjust or do next.
03

Data ROI Audit

3–4 Weeks · Fixed Fee · Natural Starting Point

A structured diagnostic for organisations that want an honest picture of where their data investment is working and where it is not. The output is a prioritised roadmap with a measurable success metric attached to each recommendation.

  • A clear picture of which data initiatives are generating return and which are not
  • The two or three opportunities most worth acting on, ranked by likely impact, including any AI capabilities worth pursuing
  • A roadmap the leadership team can act on, with a success metric attached to each initiative
  • A report you can take to your board without translation

A contained piece of work that gives both sides a clear view of what is actually needed before committing to anything longer. Structured as a fixed fee, scoped after an initial conversation. Designed for organisations that have already invested in data and want to understand what it is returning.

How this works
1. Define the question What decision does the leadership team most need to make? 2. Set the metric What does a good outcome look like, and how will we know when we get there? The metric is tied to a business decision: cost, revenue, or risk. We agree it before any diagnostic work begins. 3. Deliver and review Structured diagnostic, clear report, prioritised next steps. 4. Review and agree next steps Walk through what the work found, what it means for the business, and what to do with it.

Not sure which engagement is the right fit?

The right place to start is wherever your most pressing question is. If you are not sure, a short conversation is usually enough to work it out.

Let's Talk

Let's find out if there's a fit.

I work with a small number of organisations at any one time to ensure every engagement receives full attention. The first step is a short conversation — no agenda, no pitch — to understand what you are trying to solve.

What to expect.

The first conversation is usually 30 minutes. No agenda, no pitch. Just a chance to understand what you are trying to solve and whether there is something useful I can help with.

kamini.garg@visthena.ch
Zurich, Switzerland
LinkedIn — Kamini Garg

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