Interview with Anne Marec, founder of Yelowi
Technological innovation is often cited as a driver of transformation. Yet in a shifting industrial environment, it is models — economic, organizational, managerial — that truly determine an organisation’s ability to leverage technology. Faced with accelerating development cycles, volatile markets and the rise of AI, inventing is no longer enough: companies must structure, adjust and align. Model innovation thus becomes the prerequisite for technological innovation — a lever to orchestrate it, embody it and make it viable. This interview explores that strategic complementarity through an operational lens: recruitment within industrial innovation projects.
Thank you, Anne, for joining us. Could you introduce yourself briefly?
I am Anne Marec, co-founder of Yelowi. Passionate about science and innovation, I have spent more than 14 years supporting companies in their transformation projects, especially on financing and structuring, alongside my associate Florian Pelardy. Working in consulting has shown me how difficult it has become for companies and independent experts to meet at the right time and under the right conditions. Yelowi emerged from that observation: the desire to streamline collaboration, save time and connect the right people with the right projects. For us, innovating is not just about technology or budget — it is about teams, agility and timing. With Yelowi, we aim to make innovation more accessible, human and shared, because we believe that real solutions are born from complementary talents.
1. Why is model innovation essential in industry today?
Because innovation no longer relies solely on technology. Product cycles are shorter, markets more unstable, and companies must constantly adapt their industrial logic. It’s no longer just about designing a technology, but rethinking organisational, economic and managerial models. Larry Keeley’s “10 types of innovation” framework illustrates this diversity well: one can innovate through a new business model (e.g. shifting from product to service), by redefining partner networks, or by radically transforming the user experience — far beyond code or tools. This shift also redefines the skills required: a strong profile is no longer just a technical expert, but someone able to evolve, structure and lead a team over time. That is what enables real innovation.
2. What recruitment challenges in industry inspired the creation of Yelowi?
Industrial companies face three recurring challenges: difficulty developing skills over time; high turnover in technical and innovation roles, making knowledge transmission harder; and rising needs for specialised, high-value, short-term expertise. Existing solutions aren’t adapted: traditional freelance platforms neither qualify strategic needs nor assess a freelancer’s capacity to integrate into complex contexts. We therefore designed Yelowi as an augmented matching solution built on a soft-skills framework tailored to industrial innovation. Developed with the University of Le Mans and enriched by European research (eLene4Work, O*NET, ESCO, HESTER H10), this framework is designed to be directly operational — far from academic or generic approaches.
3. Where should companies begin when evolving recruitment or project management practices?
Everything starts with a precise diagnosis. Most recruitment failures stem not from technical gaps, but from poorly defined needs or team mismatches. Three dimensions are essential: clearly identifying the project phase (creation, structuring, implementation); understanding existing team profiles; and formulating concrete objectives for the mission (what is expected in 3 or 6 months). This shift highlights the need to rethink selection criteria: in fast-moving environments where teams constantly reconfigure, fit is no longer just technical — it depends on a person’s ability to adapt to the project’s timing, interact with existing team dynamics and create value from day one. This often-overlooked adaptability becomes a strategic lever for success.
4. What does your behavioural matching method involve?
Our approach relies on two pillars.
Advanced soft-skills qualification combining:
– a short, actionable self-assessment;
– automated analysis of personal descriptions (NLP + behavioural models like DISC);
– modelling of innovation-related profiles: creator, implementer, improver, connector, coordinator, leader.
2. A dual project/profile diagnosis:
On the company side, we analyse team configuration and identify complementary profiles. On the freelancer side, we assess their ability to operate effectively in the project’s dynamics — whether in R&D, go-to-market or internationalisation. Our goal is not simply to optimise “human fit”, but to anticipate the real quality of collaboration in a specific context.
5. What role does AI truly play in professional matching?
AI brings unparalleled precision — far beyond time-saving. Our AI doesn’t just match keywords: it relies on NLP to interpret needs, vector embeddings and LLMs to assess contextual relevance, and an explainable model where every recommendation is justified. Companies receive profiles with compatibility indicators and interview points; freelancers are matched with missions where they can create real value. In short: our AI is not made to recruit faster, but to recruit smarter.
Conclusion
By placing the model at the heart of innovation, this approach highlights an often-overlooked dimension: human organisation as the condition for technological viability. Recruitment becomes not a tactical response, but a lens revealing the systemic dynamics driving industrial projects. It invites organisations to rethink practices — not through rupture, but through continuous adjustment aligned with real team needs and project timelines. A discreet but decisive endeavour for anyone steering innovation in complex environments.
