What drove the decision to develop an AI-based use case?

We have built Sagacity’s AI platform in response to a growing disconnect: the pace of change in the workplace is outstripping people’s ability to keep up. Traditional learning systems are too slow, too generic, and often detached from real-world application.

We see AI as a powerful enabler, which is capable of delivering personalized, feedback-rich, and adaptive skill-building experiences at scale. AI has allowed us to rethink learning as a continuous, embedded process, rather than a one-time event. The decision has been driven from the need to solve a human problem with the right technology.

 

What were your expectations or requirements for the AI application?

We needed the AI solution to support real-time feedback that is relevant and actionable, adaptability to individual skill levels, and scalability in the context of accelerating skills development. These capabilities are essential to make learning more effective, engaging, and aligned with real-world demands.

We expected the AI to simulate workplace realities, offer targeted practice, and give meaningful insights to both learners and organizations.

Importantly, we also needed explainability and control. Employees must understand the rationale behind the feedback they receive, and organizations must see how skill evaluations are derived. This transparency builds trust and reinforces the credibility of the learning process. The AI needed to act as a mentor that guides growth through clear, understandable logic, not as a black-box system issuing opaque judgments.

 

Which partners and technologies did you rely on during development?

We used our Practice-Feedback-Progress model rooted in adult learning theory, supported by transformer-based AI and retrieval-augmented generation. Development was followed by iterative testing. Feedback and skills grading were calibrated through expert-led training and aligned to best-practice competency frameworks to ensure reliability, fairness, and instructional value.

 

The use of AI solutions must also be accompanied by a change in competences. How did you handle the skill shift within the team?

Internally, our team already possesses strong AI expertise, allowing us to build a solution that feels intuitive to users and hides the complexity behind a seamless experience.

Unlike many AI solutions that demand new technical competencies from their users, our platform is designed to eliminate that barrier. It empowers subject-matter experts, regardless of technical background, to create interactive, skills-focused learning experiences with ease. The AI is embedded in the workflow, not exposed as a tool that needs configuring. This approach makes advanced capability accessible while preserving simplicity.

 

In what timeframe did they implement the AI solution in your company/your client‘s company?

From the initial concept to a working prototype, our first AI use case took around six months. We then spent an additional three months in pilot testing and iteration, co-developing with early users to refine use cases and align AI behavior with learning goals.

 

A conclusion to your AI solution:

Sagacity’s AI solution transforms skill development from a slow, generic process into a fast, targeted, and measurable growth driver. By identifying role-specific skill gaps and delivering practical, scenario-based learning with real-time feedback, the platform ensures that learning translates directly into performance. It does not require technical expertise to deploy or use, making it accessible from day one. Customers report productivity gains of over 7% within just a few months, proving that our AI doesn't just accelerate learning, it enables organizations to build lasting, role-critical capabilities at scale.

 

One final piece of advice/tip to other entrepreneurs looking to apply AI:

Focus on real human problems; use AI to augment human capabilities and improve lives, not just automate. Build solutions that are intuitive, transparent, and genuinely helpful. As AI lowers technical barriers, more players will enter the market, so quality and speed become critical. Excellence and execution will matter more than novelty.

 

 

Further information:

https://sagacityintelligence.com/

 

Picture: Mainition