Business in the Loop™

The challenge of integrating AI into real-world applications is significant, with an 80% failure rate in deploying AI models (as reported by Harvard Business Review, 2023/11), largely due to the absence of business expertise from the development process. So, the models are not understood and trusted, and therefore cannot be put into production even after considerable efforts by data science and IT teams.

At TAZI, we’ve innovated with our Business in the Loop™ philosophy, prioritizing the inclusion of business experts right from the start.

We are using the word “Business” instead of “Human” in the Loop because in this context we mean that business experts need to be at the table, not just a “human” in an organization.

Unlike traditional approaches that may sideline these experts, our platform ensures they are central to the AI solution lifecycle. This strategy not only fosters a deeper understanding and trust in AI models among business teams and data science teams, but also significantly enhances the alignment of AI solutions with business objectives and workflows. By enabling rapid iterations and adjustments based on direct feedback from operations and business teams, TAZI accelerates the refinement of AI models to meet specific business needs.

“Success rate of AI deployments to 80%”

The result is a dramatic increase in the success rate of AI deployments to 80%, underscoring the efficacy of our approach in delivering tangible, real-world ROI from AI investments. TAZI’s platform is intuitively designed for easy comprehension and use by business professionals, democratizing AI and ensuring its benefits are fully leveraged across the organization.

“One often doesn’t know what they are looking for but they know it when they see it.”

FAQ

What is a minimum viable data set for a first use case?Only the fields needed to trigger one action and measure one KPI. Start small to move faster.

How do I keep personalization non-creepy?
Ask short, tailored questions and let customers confirm context before you act. Log consent and make value clear.

How do I protect customer data privacy? Where do I host the models and data?
Keep data and models behind your firewall when possible. Limit external transfers. Use clear access controls and logs.

Which KPI should I pick first?
Choose one outcome tied to revenue or cost. Examples. churn reduction, faster complaint resolution, or deposit growth.

How do I avoid pilot purgatory?
Pre-agree success thresholds at kickoff. Assign an executive sponsor and a frontline owner. Set weekly reviews.