Continual

Continual

Continual

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Continual AI app

Cloud-based predictive modeling using SQL.


Why Install Continual AI to replace a human task?
Artificial Intelligence and Machine Learning Business and Event Management Data and Analytics Data Science Predictive Analytics

AI Information

What is Continual AI?

Continual AI Platform:

Continual is an operational AI platform that simplifies the process of building and maintaining predictive models using simple SQL or dbt declarations. It allows users to create predictive models on popular cloud data storage platforms like BigQuery, Snowflake, Redshift, and Databricks without the need for complex engineering or infrastructures such as MLOPS platforms. Continual models are continually improved, ensuring that predictions are always up-to-date. Data and models are stored directly on the warehouse, making it easily accessible to operational and BI tools.

Continual is a versatile platform that can be used in various business scenarios like predicting customer churn, inventory demand, and customer lifetime value, helping businesses to make informed decisions. It is ideal for modern data teams who love SQL and dbt, but equally accessible to data scientists who can extend the platform by integrating Python. Continual's declarative approach to AI makes it easy to work with for analytics and data teams, allowing them to focus on building

TLDR: AI for Cloud-based predictive modeling using SQL. Copy and paste these prompts into Continual.

Continual Prompts

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Continual - Opensource ChatGPT Plugin

Who is Continual AI for?

1. Data analysts who want to build predictive models without needing complex engineering or infrastructures.
2. Data engineers who want to simplify the process of building and maintaining predictive models through simple SQL or dbt declarations.
3. Business intelligence professionals who want to access up-to-date predictions directly from their warehouse, without needing to rely on external tools.
4. Data scientists who want to extend the platform by integrating Python and building more complex models.
5. Business managers who want to use predictive models to better understand customer behavior and make data-driven decisions.

Cloud-based predictive modeling using SQL. on these platforms

What are the use cases for Continual?

1. Customer Churn Prediction - Continual can be used to predict which customers are at the highest risk of churning. By analyzing customer behavior and interactions with the business, Continual can identify patterns that indicate a customer is likely to leave. This information can be used to implement targeted retention strategies to keep customers engaged and loyal.

2. Inventory Demand Forecasting - Continual can be used to forecast future demand for products or services. By analyzing historical sales data, market trends, and other relevant factors, Continual can generate accurate predictions of future demand. This information can be used to optimize inventory levels and avoid stockouts or overstocking.

3. Fraud Detection - Continual can be used to detect fraudulent behavior in financial transactions. By analyzing transaction patterns and identifying anomalies, Continual can flag potential instances of fraud. This information can be used to implement measures to prevent fraudulent activity and minimize financial losses.

4. Predictive Maintenance - Continual can be used to predict when equipment or machinery is likely

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