We build products that scale

Seven ventures in the portfolio, born from our own research and validated with paying customers.

Our approach

We start from a real need, ours or a client's, and take it to product in five steps, through to scale with capital and an industrial partner.

1

Opportunity identification

We start from market gaps, operational inefficiencies or emerging technologies (AI, automation, data analytics).

2

Rapid validation

A lean MVP, tested internally or with beta customers, to validate product-market fit.

3

Proprietary build

Proprietary stack, multidisciplinary team, agile method. AI-native products built to carry load.

4

Industrial Venture Partner

We look for an industrial partner who has the problem we solved. We design the go-to-market with them, and they become the stakeholder of the launch.

5

Scale with investors

We go to PE and VC only with a validated industrial partner in place. We connect financial capital to the industrial world.

Our own tools become products

Many start inside our daily operations and reach the market later.

Native product-market fit

If it works for us, it works for the market

Continuous iteration

We are the first users, so we constantly improve

Commercial credibility

We sell what we actually use

Economies of scale

R&D investments amortized across internal use + external clients

From research to venture, in four moves

We start from a problem AI makes solvable for the first time and carry it to a revenue stream. We pay for the research once, so every venture starts with proven technology inside it.

  1. 01

    Scientific research on the problem

    Literature, universities, reproducible experiments, public benchmarks. The lab produces reusable assets and writes down what worked, so no venture pays for the same lesson twice.

  2. 02

    Validation with corporate and enterprise clients

    Research meets a real buyer. We take the problem inside organisations that have it, as consulting work, and check whether the technology holds, who buys it and at what price.

  3. 03

    AI-native productisation

    Technology that works and a clear buyer: we package it. Small team, agents and our own stack from day one, a business model picked from B2B licence, subscription, media and metered API.

  4. 04

    Deep tech or tech service spin-off

    The venture leaves as a company of its own. Deep tech when the value sits in the technology, tech service when it sits in the ability to deliver. KVA keeps a significant stake and stays in operations.

Inside, every venture climbs six rungs: ideation, validation, MVP test-to-learn, MVP test-to-confirm, scale 1, scale 2. Each rung carries the criteria that close it, and until they are closed you do not move up.

Our proprietary products

Each sits at a different rung of the ladder. What the lab learns on one ends up inside the next.

Why we build ventures

There are three reasons: research gets a real proving ground, the team learns on systems in production, and the portfolio earns revenue independent of consulting.

Test emerging technologies in real environments (AI, automation, blockchain)

Develop entrepreneurial talent within the KVA team

Generate recurring value through diversified revenue (SaaS, services, licensing)

Demonstrate operational credibility to corporate clients and investors

Create scalable assets that can become standalone companies

Every venture leaves reusable assets: models, agents, pipelines. The next one starts from there.

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Explore the stack powering our ventures

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