Companion Partnership: Develop best practices together—instead of experimenting alone.

The Companion Partnership is for companies that want to embed and scale AI strategically, not pilot it. Specifically: organizations at the "Professional" or "Shaper" maturity level that have moved beyond initial pilots, have built internal experience with AI implementations, and want to know how other companies at this level are taking their next steps.

This is not an entry-level offer for first contact with AI. It is for those who know that the real challenges lie in scaling, governance, and sustained value creation, not in the proof of concept.

Traditional consulting is transactional: a project is defined, a team arrives, delivers a result, and leaves. What remains is a document, but rarely built capability.

The Companion Partnership is continuous and collaborative. We are a long-term companion, not a contractor. We think alongside you, challenge assumptions, share knowledge from other companies' experience, and help you build internal AI capability. Our goal is for you to need us less over time, not more.

Open exchange about real challenges, including poor decisions, failed projects, and internal conflicts, only works when confidentiality is structurally secured, not just promised. Our events and formats take place in a protected setting explicitly designed for this kind of dialogue.

That sets the Companion Partnership apart from conferences or public networking formats, where self-promotion limits openness. Here, people share what actually happened, not the polished version. For many participants, this is one of the greatest benefits of the format.

Yes, within a clearly defined scope. The Partnership includes continuous sparring with our experts on strategic and substantive questions. Our engineers can review your architecture or code and give concrete feedback: what works, what we would approach differently, where we see risks.

The Partnership is not a development contract. In this format, we do not build for you; that is AI Development. We think with you. The goal is to sharpen your judgment, not deepen your dependency.

No organization can cover every aspect of AI on its own. Working with the right partners means faster, more reliable results: access to relevant expertise, tested approaches, and technologies that would be costly or slow to build internally. That reduces risk and raises quality without requiring you to own everything yourself.

The appliedAI ecosystem brings together large enterprises, mid-sized companies, start-ups, research institutions, universities, technology providers, and public sector organizations. This breadth is not incidental: diverse perspectives and competencies make it easier to learn from one another, develop solutions together, and scale AI applications across organizational boundaries.

Companies gain access to knowledge that is hard to build internally: proven approaches from practice, direct expert guidance, and a network of organizations that understand similar challenges. This accelerates AI adoption, helps avoid common mistakes, and strengthens internal decision-making across strategy, governance, and technology.

Networking produces contacts. The Companion Partnership produces shared work on questions that have no established answers yet: AI governance, agentic AI in production, evaluation infrastructure, organizational AI maturity. Areas where practice is still taking shape.

The format includes sparring, curated knowledge, and working groups where companies work together on concrete problems. If you want to collect business cards, this is the wrong place. If you want to work on the genuinely difficult questions, it is exactly right.

The further an organization has advanced in AI maturity, the smaller the pool of relevant peers, and the more valuable access to others at the same level becomes. For organizations already scaling and setting their own standards, the Partnership offers three concrete advantages: peer comparison with companies in a comparable position, joint problem-solving on shared challenges, and faster learning through direct access to others' experience.

Those operating at "Shaper" level know: the relevant questions are not answered in any whitepaper. They are worked out in conversations between the people currently solving the same problems.

Working groups produce practical knowledge that is immediately applicable: shared patterns, reusable templates, and documented approaches, meaning solutions that have been tested and validated in real projects.

The difference from traditional knowledge formats lies in how the knowledge is created. It is not prepared by experts and then consumed; it is developed together, by companies that face the same challenges. What emerges is more robust and closer to practice than anything a editorial process can produce.