Clients' Purpose-Driven priorities are what we strive to deliver and fulfil.

Tenzai conceptualized and developed an AI-powered replenishment solution based on the principles of purpose-driven AI framework. The new solution predicts store level replenishments for each stock keeping unit (SKU) across their retail stores.

Tenzai data scientists adopted a three-step approach to design a solution for them. Data from multiple sources like invoice, customer and product data required for analysis was integrated.

Tenzai developed a custom ML-based forecasting solution with the Purpose-Driven AI approach. Internal data from enterprise data systems and external data were utilized to develop the model.

Tenzai adopted the Purpose Driven AI approach to develop an AI-empowered marketing mix solution. The solution with its powerful simulation and optimization capabilities helped the business quantify the relationship between multiple variables, channels and business outcomes.

Based on the user persona, Tenzai designed strategic, operational and analytics dashboards for senior management, line managers and data analysts.

Tenzai data scientists employed the Purpose-Driven AI framework to develop an AI-based route optimization solution for the client. The team conducted an in-depth exploratory data analysis to extract key insights from the data.

Tenzai deployed the Purpose Driven AI approach to develop a Machine Learning-based recommendation engine for the client.

Tenzai conducted a Purpose-Driven AI workshop to brainstorm with the clients to conceptualize and design the solution. Based on the insights, developed a NLP-based product intelligence and sentiment analysis solution.

Using Purpose Driven AI, a trade promotion solution was built to optimize current trade campaigns and uncover entirely new opportunities.

Tenzai built an integrated customer acquisition solution employing statistical analysis and machine learning. The new acquisition model helped the clients to design campaigns and marketing strategies specific to each prospect group.

Data Scientists implemented a multidisciplinary approach to help the client implement an effective customer journey and engagement framework. Employing multiple disciplines ranging from consumer behavior, digital marketing, statistics and machine learning helped Tenzai build an effective customer journey analytics application.

Tenzai employed a unique approach, to identify potential churners and then prioritize the right customers for retention. The segment-specific churn prediction model resulted in higher accuracy compared to conventional methodologies.

Tenzai employed the 6D Segmentation framework to develop a robust customer segmentation model for the client. The segmentation framework provided the retailer with a better understanding of the current value and future potential for each segment.

Tenzai helped the client to define the roadmap and execution plan for creating a data science CoE to accelerate digital transformation within the enterprise. The data science team helped bring a transformational change to the enterprise by empowering business users to arrive at strategic decisions backed by insights.

Tenzai developed a machine learning solution to help the client identify the right candidates to admit. The solutions helped the client to gain deep insights into the profile of candidates who are most likely to accept their admit offers and key factors influencing their admission decisions. It also helped them to automate admission workflows and enhance productivity for admission teams.