Traditional analytics often falls short of empowering users across an organization, creating bottlenecks and limiting the value of data. McKinsey approached Tailor Hub with a clear goal: developing an AI assistant that could streamline workflows, reduce inefficiencies, and unlock insights from both structured and unstructured data. The assistant needed to enable users to ask natural-language questions and receive accurate, actionable answers—leveraging large language models, SQL, and machine learning frameworks to bridge the gap between raw data and business decisions.

McKinsey & Company is one of the world’s leading management consulting firms, renowned for helping organizations solve complex business challenges and drive innovation. With a strong focus on strategy, McKinsey collaborates with global enterprises to transform their operations, leverage emerging technologies, and deliver measurable impact.

Tailor Hub delivered an innovative AI-powered solution, seamlessly integrating their existing APIs and advanced language models hosted on AWS Bedrock. The solution enabled teams to ask questions and receive dynamic, visual, and real-time answers. The intuitive interface removed technical barriers, empowering both data experts and non-technical users to unlock the full potential of AI-driven insights.

At the heart of this solution was Next.js, the technology that powered both the frontend and backend of the interface. Tailor Hub connected client’s existing APIs—focused on summaries and reasoning—with advanced LLMs, enabling the system to process queries and generate meaningful, visual responses.

This project was a perfect example of collaboration between Tailor Hub and McKinsey, where our team brought the technical expertise to complement McKinsey’s strategic vision. By aligning innovation with execution, we enabled the client to achieve an AI-driven solution far beyond static dashboards, redefining the way their teams interact with data.

Working altogether with the client’s data teams in India was a blast, so was to see what wonders can AI bring to the table when the right pieces are touched.