We confront your AI vision with real people and settings early on, so you can be confident it will deliver on its promise.

Ensure your vision seamlessly aligns with reality through a value proposition that addresses the genuine needs of stakeholders. Unfortunately, many AI initiatives fail to achieve this alignment and ultimately fall short.

By prioritizing real-world validation with real people from the outset, you challenge assumptions and turn hype into grounded, actionable insights. This gives you, your investors, and decision-makers the evidence needed to confidently support your vision, making success just a matter of execution.

Great requirements empower you to build successful AI products and services by ensuring they are rooted in real-world needs and validated insights. More than any other technology, AI depends heavily on the context in which it is used and by whom.

That’s why understanding requirements within a social context is crucial. By actively collaborating with local stakeholders and exploring local environments, we provide you with actionable requirements, bridging strategy and development. At the center of this user-centered approach is rigorous evidence collection, ensuring that every feature and functionality is validated before you commit resources.

Data science teams are often not fully familiar with the domains for which they are creating AI solutions, leading to assumptions that can diverge significantly from reality. Our customized training programs are designed to quickly familiarize your data science team with the most critical aspects of a domain for your specific AI innitiative. This ensures your team has the best starting position possible to deliver a succesful AI solution.