Our Services

For Startups and Scale-ups

We help founders build products people actually want and will pay for. What that means depends on where you are.

Before there’s a product or revenue. The job is finding out whether the thing is worth building while changing your mind is still cheap. Customer interviews, surveys, small experiments, early sales conversations. Whatever gets a real answer fastest. A survey is the easiest of those to run and the easiest to ruin, so we build ours around questions designed to get information rather than agreement. You come out with a defined customer, a problem you’ve confirmed people actually have, and a price someone has agreed to pay.

And when the numbers say “no”, the answer is usually “not like this”. Validation doesn’t just tell you customers don’t want your product. It tells you what they do want, so you know which direction to go.

When the product is built and growth has stalled. Validation isn’t the problem anymore. But something is slowing you down. It’s usually positioning that doesn’t land, pricing set below or above the value you deliver, the wrong framing of the problem, the wrong way of presenting the product, or a sales motion that only works when the founder runs it. We start from the traction you already have: what your best customers have in common, why the others didn’t convert, and what has to change in the offer. From there we work our way toward a money-making system.

Like all consultants, we provide deliverables: customer profiles, problem statements, product specifications, pricing models, demo playbooks, partner programs. But every one of ours does more than state how things are — it names the actions you need to take to steer them in the right direction. When we finish, you can start implementing right away.

We know money is always tight in startups (we’ve worked with quite a few). Like every consultancy we have an hourly rate, but we rarely use it. If the work can be scoped, we would rather name a fixed price and take the shortest path that solves the problem, so you know what you’re paying and getting there quickly is in everyone’s interest. Whether the money comes from a program or out of your own pocket, if the fit is right we’ll find a way to make it work.

Where we come in

Problems we solve

I have an idea, but I don't know if it's worth building
We run problem validation before a line of code gets written — structured customer interviews and experiments that tell you what people will actually pay for, not what they politely say in a survey.
I'm building, but I'm not sure who it's really for
We define your ideal customer profile from real conversations, then pressure-test it. Most products that struggle later were aimed at a segment nobody ever checked.
I have so many ideas for my product, I don't know where to start or when to stop
We sort the list into what gets built now and what waits. The target isn't the minimum viable product but the minimum sellable one — the shortest route to something a customer will actually pay for.
I'm ready to launch and I don't know how to land it
We plan the launch as a learning phase, not a marketing moment: hypotheses, success criteria, and tracking in place before the first user arrives.
I launched, but the first customers aren't coming
We work the unglamorous part: who to approach, what to say, what to charge. That gets settled in real sales conversations, never on a funnel diagram.
I'm selling, but growth is slowing instead of accelerating
That is usually pricing or positioning, and working harder will not fix either. We rebuild the offer and the pricing model around the value you actually deliver.
Users tell me they love it, but the numbers disagree
We track usage before, during and after launch, then reshape the product around the gap between what people say and what they actually do.
I keep hearing we should be using AI and I don't know what that means for us
Not prompt training. We look at how your business actually runs and where AI changes the shape of it — what you can now do that was not worth doing before, and what stops being worth doing at all.
Something else, or I'm not sure which of these it is
Start a conversation. Working out which problem you actually have is the first half of the job, and we do that part with you before anyone signs anything.

Selected work

What that looked like

Agritech, fintech, edtech, deep tech, hardware, B2B SaaS, developer tools, marketplaces, health and fitness — from a first idea to a company with real traction and a growth problem. The sector changes. The problems rarely do.

Cropt · BioSense Institute spin-off
Repositioning an agritech AI platform
Challenge: Strong satellite-analytics technology, scattered positioning, no segment focus, and prices far below the value delivered. What we did: Stopped selling the platform and started selling what it can make — narrow, on-demand products, each solving one problem for one segment, all running on the same satellite analytics. Built the three-tier offer model, the pricing and the sales frameworks to match, with a clear filter for which segments are worth serving. Outcome: A framework for making new products on demand and getting the value to the customer, clear segmentation, pricing anyone on the team can explain, and a plan for expanding the territory.
SEAL · video authentication
A channel-led go-to-market for deep tech
Challenge: A technically strong blockchain video-authentication product with no commercial validation, no pricing and no route to market. What we did: Defined an EU-first, channel-only go-to-market through system integrators with a Slovenia/Croatia beachhead, then built the partner enablement materials to run it. Outcome: A complete commercial playbook — pricing, partnership program and sales guides — ready for integrator conversations.
Whisperly by Lexelerate · via NALED StarTech
Pricing and sales for a compliance SaaS
Challenge: A capable data-privacy platform underselling itself with feature-led demos, discounting habits and no segment focus. What we did: Introduced value-based pricing, rebuilt the demo into a playbook through live teardowns, and refocused the strategy on banks and insurers. Outcome: A sharper sales motion the team now runs on its own: pricing they can explain, an answer to discount requests that doesn't concede, clear positioning against the incumbents, and the confidence to lead with credentials they had been too modest to use.
Blistavi Um · story-based child development app
Replacing survey answers with real usage data
Challenge: The team was heading into launch on the back of glowing survey results, parents saying yes they wanted the digital version, with no read on whether that matched real behavior. What we did: Instead of trusting satisfaction scores, tracked what people actually did before, during and after launch. Every click, every session, every drop-off. That data reshaped both the target audience and which features mattered. Outcome: Built on real usage instead of survey answers, the next iteration saw 3x longer usage, one of the metrics that matters most in a product like this.
Mosq-Switch · mosquito repellent cabin, hardware
A first deployment that sold the next three
Challenge: A physical, location-dependent product needed a fast go-to-market strategy, and the first deployment would either build trust or kill it before it started. What we did: Defined the optimal placement locations and locked down what had to be on the unit itself. Safety information, what the repellent contains, everything someone meeting it for the first time needs in order not to walk away. Outcome: The first deployment became a proven case study, used to close three additional locations.
MyTurn · parent-child chore and habit-building app
Finding out why every previous attempt had failed
Challenge: Previous apps and trials in the space had all failed. The question wasn't whether to build another one, but why this one would succeed where the others didn't. What we did: Ran competitor analysis alongside deep customer interviews and found the core issue — existing solutions were built for parents, not for the children who actually had to use them daily. Outcome: Now used by 4,000+ parents and children in Montenegro, and ready for official launch in the US.
SCI FARI · educational STEM game for kids
A validated "no" before the build began
Challenge: Sitting at the crossroads of education and entertainment, the team needed a business model that balanced both, and had to decide which market to go after first. What we did: Helped the team design the interviews, desk research and low-fidelity demos, then run them, pressure-testing the model before anyone committed to building it. Outcome: The concept turned out to need far more time and money than the team had. They found that out before building rather than after, and were free to put both into something with a better chance.
JigJoy · AI agent infrastructure (Mozaik, Baro)
Three pivots to find the audience that stuck
Challenge: Find a niche where an AI product could scale fast on minimal marketing spend, without going head to head with the big AI players. What we did: Designed the experimentation cycles with the team and helped them run them — different MVP versions in front of different audiences, built to pivot fast rather than to be right the first time. Outcome: Pivoted through three audiences (school teachers, influencers, private tutors) before landing on developers, and from a consumer product to a developer tool. That version stuck, now at thousands of users.
BeeBoo · peer-to-peer marketplace, parenting and kids
Pivoting a marketplace and unlocking new revenue
Challenge: A platform for buying and selling children's products with a scattered value proposition, no monetization beyond transactions, and a product backlog that was never prioritized against business goals. What we did: Mapped the stakeholder ecosystem and business model, redesigned the offer for both buyer and seller segments, set 12-month OKRs and turned them into a prioritized roadmap, helped the team design and run A/B tests with 43 users, and helped them build an advertising and sponsorship monetization strategy with a mapped sponsor ecosystem. Outcome: A validated pivot to a fully automated platform model, a prioritized 12-month roadmap, a complete sponsorship monetization framework with a segmented sponsor database, and a new platform concept approved for development.
Gama Point · MyBizNest · B2B SaaS for solo entrepreneurs
Turning a product launch into a structured experiment
Challenge: A business-assistance platform for the newly self-employed approaching launch with no defined ideal customer profile, no validation framework, unclear website messaging, and a delayed product after an unplanned change of technical partner. What we did: Defined a precise ICP with the team as the foundation for every product, messaging and pricing decision, restructured the launch from a marketing activity into a learning phase with explicit hypotheses and success criteria, and built an Early User Framework across three adopter segments, with metrics tracking every stage from acquisition through activation, retention, referral and revenue. The team then rewrote the website copy around the customer's own pain language. Outcome: A soft launch repositioned as a controlled product-market fit experiment, with tracking setup and onboarding priorities defined before the first user arrived.
Younger · B2C menopause fitness app
Repositioning a fitness app for premium in the US
Challenge: A menopause fitness platform targeting US women 45+ with low free-to-paid conversion, no clear differentiation from competitors, no metrics framework, and a go-to-market split across two agencies and 13 influencer partners. What we did: Mapped the funnel from first touch through to revenue and made trial conversion the North Star metric, built a KPI dashboard across every stage, designed onboarding experiments to test whether a premium tier that asked more of the user up front would convert better, and repositioned the brand on sports medicine credibility rather than the usual weight loss narrative. Outcome: A clear pivot from freemium to paid only, with a mandatory trial of three days, a unified KPI framework across all channels and partners, and concrete next steps for scaling in the US.