Our innovative product revolves around harnessing the power of AI to elevate decision-making, primarily through an advanced recommendation engine fuelled by our cutting-edge AI model. This is achieved through a proven template using specific data points, streamlining the model’s functionality and optimising the ‘next best action’ strategy.
What makes Xction.ai unique
Xction.ai pledges to enhance operational efficiency and productivity by automating the ‘next best action’ procedure, thus reducing manual intervention. The model’s foundation lies in real-world datasets and will undergo refinement throughout the subscription duration.
Existing Snowflake Marketplace for easy distribution
We use private or public Marketplace listings to list our Xction.ai data application in the Snowflake marketplace and create a frictionless experience for our customers.
Streamlit and Snowpark built-in tools for Rapid Development
Streamlit and Snowpark give our data scientists tools to prototype without being experts in front-end web development. It allows them to test new ideas with customers without going through a standard release cycle.
Snowpark Container Services run the end-to-end lifecycle of our AI/ML models
Our proprietary ‘next-best-action’ recommendation engine has a real-time feedback loop using Snowflake data sharing / data marketplace capability that continually ingests new customer interactions, and adjusts insights based on those changes.
Xction.ai is accessible through an annual subscription. Our commercial options are available in different subscription tiers and priced in USD. These tiers are meticulously designed to match the varying complexities and developmental stages of our clients’ environments:
The pricing structure considers factors such as the number of interaction channels for delivering the ‘next best action’, the volume of interactions, and the intricacy of the dataset required for training the model.
In summary, our Xction.ai data app for the ‘next best action’ in Sales & Customer Service is deployed seamlessly to organisations whose customer data are already available in their data cloud platform, yet they lack the capacity to have deeper understanding of their customer behaviour due to prohibitive costs of existing solutions and shortage of AI skilled resources to develop in-house.