Ramona Furter
See the engagement
Application · Kaplan · AI Consultant · UAE

I turn a business deep-dive into shipped, measured AI.

I lead AI-driven business models at Swiss Post today: sizing the opportunity, scoping the build, judging build-versus-buy, rolling it out and proving it moved a number. Before that, more than a decade in product and venture building. This site is my application for AI Consultant at Kaplan, and I'm relocating to the UAE.

See a Kaplan AI engagement Case studies & results
AI leadAI business models, Swiss Post
10+ yrsproduct & venture building
+9% / +15%lift on a CHF 100M+ business
UAE-readyrelocating now
Portrait of Ramona Furter
Why I fit

What the role asks, and where I've done it

The brief is to deep-dive Kaplan's operations, find the real pain points, and recommend high-impact AI with a clear cost-versus-benefit case and the guard rails to run it safely, then make that land with senior leadership. That is the shape of the work I do now. Here's how it lines up, point by point.

01

Advisory track record in AI

A demonstrated record advising on and owning AI strategy: sizing opportunities, building the roadmap, and driving an AI-first mindset with leadership. I've done this both inside a large organisation and for my own products.

Proof: AI Project Lead for business development at Swiss Post Advertising, building and running the AI roadmap, KPIs and the leadership case.

02

Up-to-date AI/ML understanding

Strong, current grasp of Generative AI, LLMs and predictive analytics, and, more importantly, where they actually pay off in a business. I'm a practitioner: I prompt, retrieve, ground and chain, and can talk evaluation, hallucination, latency and cost as real constraints.

Proof: build daily with Claude, GPT and n8n; built Pedal Peak end to end with AI workflows; the engagement below is my own work.

03

Deep dive, data-driven problem solving

I go into the processes, the workflows and the data to find the inefficiencies and the pain, then let the evidence decide where AI belongs. Comfortable in analytics, SQL-level questions and A/B design.

Proof: +9% conversion and +15% checkout lift through research, A/B testing and analytics on a CHF 100M+ business at ifolor.

04

Translating tech for executives

Turning ambiguity into a clear, compelling plan and selling it upward is the part I'm best at. I've made the case to C-level and investors, owned enterprise partnerships, and held the line on scope. Storytelling with data is how I move decisions.

Proof: reported to C-suite at ifolor; owned UBS and Baloise partnerships at Brixel; raised two funding rounds as a founding team.

05

High-impact recommendations, cost vs benefit

I recommend where to start and where not to: impact against effort, build versus buy, and an honest cost-versus-benefit for each initiative, with the guard rails that keep it safe. I scope to the smallest thing that proves value, then scale what works.

Proof: own AI-driven business models at Swiss Post from opportunity sizing to a prioritised, KPI-backed roadmap with feasibility calls.

06

Fast on new business models, short engagements

Much of my career has been landing in an unfamiliar business, understanding it fast, and delivering high-value results on a tight clock. Venture building is exactly that: many models, little time, real outcomes.

Proof: built and scaled several ventures at Sparrow Ventures; ran market pilots from MVP to launch inside Die Mobiliar.

Proof material · as your posting asks

Case studies, with results

Your posting asks applicants to bring proof of previous services and results. Here are four, each as a short situation, what I did, and the outcome. The engagement further down shows how I'd apply the same method to Kaplan.

E-commerce · CHF 100M+

Lifted a CHF 100M+ shop with data

Senior Product Manager, Lead E-Commerce · Ifolor Group

Situation
A CHF 100M+ e-commerce business where the conversion funnel had plateaued and decisions were driven by opinion.
What I did
Owned the e-commerce strategy end to end, ran structured research, built an A/B testing programme and dug into the analytics to find where buyers dropped off.
+9% conversion +15% checkout step reported to C-level
AI product · built end to end

Shipped an AI-built product solo

Founder · Pedal Peak (own venture, 2023 to now)

Situation
An idea for a cycling community platform, no engineering team, and a need to prove it fast.
What I did
Designed and built the product end to end using LLMs and AI automation workflows (n8n), from content and routing to the site itself, then took it live.
Live product LLM + n8n workflows hands-on, not sponsored
0 to 1 · venture

Grew a venture from zero

Founding team, Marketing & Growth Lead · WePractice (Sparrow Ventures)

Situation
A new mental-health venture starting from nothing, needing a go-to-market and traction to raise.
What I did
Built the full go-to-market on a hypothesis-and-data approach, generated demand, and built and led the marketing and sales team after Series B.
10 locations, 23 people 1000+ client matches yr 1 2 rounds raised
Enterprise innovation

Pilots from MVP to launch

Intrapreneur, Innovation · Die Mobiliar

Situation
One of Switzerland's largest insurers wanting to test new digital products without betting the business on them.
What I did
Ran market pilots for new products (Smide, now BOND Mobility, plus XpertCheck and Lizzy) from MVP through to launch, coaching cross-functional teams and testing partnerships and data.
Multiple MVP to launch cross-functional short-cycle validation
Curriculum vitae

Ramona Furter

AI and product lead in Zurich, more than a decade in product and venture building, relocating to the UAE. I turn ambiguous problems into shipped products and measured results, increasingly with AI at the core. German and Swiss German native, English fluent, French conversational.

Jan 2026 to present

AI Project Lead, Business Development

Swiss Post, Advertising · Zurich

  • Lead AI-driven business models for Swiss Post Advertising, from sizing the opportunity to building and running the roadmap.
  • Turn AI ideas into go-to-market plans and new revenue, tracked with clear KPIs.
  • Run cross-functional work from concept to launch across product, tech, data and commercial teams.

Oct 2024 to Jul 2025

Senior Product Manager, Lead E-Commerce

Ifolor Group · Zurich

  • Owned the e-commerce ecosystem and strategy for a CHF 100M+ business, reporting to C-level.
  • Lifted conversion 9% and the checkout step rate 15% through research, A/B testing and analytics.
  • Led a cross-functional team and external agencies, owning budget, resourcing and KPIs.

Jun 2023 to Sep 2024

Lead Project Manager

Brixel · Zurich

  • Owned the partnerships with financial institutions, UBS and Baloise, that drove growth.
  • Was the main bridge between senior client stakeholders and the internal product team.

Mar 2020 to May 2023

Marketing & Growth Lead, Founding Team

WePractice · Sparrow Ventures (Migros Group) · Zurich

  • Founding team of a mental-health venture. Closed two funding rounds and grew it to 10 locations, 23 people and 170+ customers.
  • Generated 1000+ client matches in year one and built the full go-to-market on a hypothesis-and-data approach.
  • Built and led the marketing and sales team after Series B, owning budget, KPIs and growth.

Sep 2019 to Sep 2022

Growth & Venture Builder

Sparrow Ventures · Zurich

  • Built and ran growth and go-to-market for several internal startups, from early validation to scale-up.
  • Used research and experimentation to improve conversion, lower acquisition cost and raise customer lifetime value.

Jan 2017 to Aug 2019

Intrapreneur, Innovation

Die Mobiliar · Bern

  • Ran market pilots for new products (Smide, now BOND Mobility, plus XpertCheck and Lizzy) from MVP to launch, inside one of Switzerland's largest insurers.
  • Coached cross-functional teams and explored new data and partnerships.
A worked engagement

How I'd run a Kaplan AI engagement

Not a slide of buzzwords. This is the method your posting describes, made concrete: deep-dive the operations of a learning business, put the AI opportunities on an impact-versus-effort board, then take each one from the pain point to a recommendation, an honest cost-versus-benefit call, and the guard rails to run it safely. Click a number on the board, or an item in the list.

Worked example · illustrative figures

Where I'd start, and why

Four AI opportunities from a deep-dive of a learning business, scored on impact and effort. I'd open with the quick win that proves the model and the guard rails, then earn the bigger bets. Prioritisation is the job.

Impact →
Quick wins Big bets Low priority Heavy lifts
Effort →
The short-term engagement

How the engagement runs

Your posting is a short, high-value engagement, so the arc is tight: understand the business fast, put a prioritised, costed set of recommendations in front of leadership, then prove the first one before I hand it over.

Phase 1 Weeks 1 to 2

Deep dive & diagnose

  • Meet the leadership, product, operations and data people, and learn the business model cold.
  • Map the processes, workflows and data to find the real inefficiencies and pain points.
  • Assemble the candidate AI use cases and the current market trends worth acting on.
Phase 2 Weeks 3 to 5

Recommend & make the case

  • Score the use cases on impact and effort and choose where to start.
  • For each, a build-versus-buy call, a cost-versus-benefit analysis and the guard rails.
  • Turn it into a clear, compelling roadmap and land it with senior, non-technical leadership.
Phase 3 Weeks 6 to 8

Prove it & hand over

  • Get the first quick-win into a real pilot behind a flag, with the guard rails live.
  • Instrument adoption, accuracy and ROI; report the wins and the misses honestly.
  • Leave a prioritised roadmap and an AI-first playbook the team can keep running.