Understanding Usage Costs

PropulsionAI is designed to provide powerful, flexible AI tools that scale with your needs. Understanding the costs associated with using these tools is crucial for managing your projects effectively. This page breaks down how costs are incurred and offers guidance on how to optimize your budget.

1. Training Runs

Costs are incurred based on the duration of your training runs.

• The hardware you select plays a significant role in determining these costs. More powerful hardware, like A100 or H100 GPUs, will incur higher costs due to their advanced capabilities. Conversely, selecting less powerful hardware like L4 or T4 GPUs will help keep costs lower.

💡 Tip: Estimate the expected training time and choose hardware that balances performance and cost according to your project’s needs.

2. Deployment Runs

Costs accumulate based on the duration your model is deployed.

• Similar to training, the cost of deploying a model depends on the hardware selected and the time the deployment remains active. Whether your model is set to scale with demand or maintain a fixed number of instances, these choices impact your costs.

💡 Tip: Scale your deployments dynamically to meet demand while minimizing idle time, which can help optimize costs.

3. Knowledge Base

While in beta, Knowledge Base usage is free, but charges will apply in the future for storage, reads, and writes.

• The Knowledge Base allows you to store, retrieve, and manage domain-specific information. Once out of beta, you’ll be charged for the storage used, as well as for reading from and writing to the Knowledge Base.

💡 Tip: Optimize your Knowledge Base by storing only the most relevant information and minimizing unnecessary reads and writes.

4. Datasets

Costs are associated with the storage of your datasets.

• When you upload and manage datasets in PropulsionAI, storage costs apply based on the size and number of datasets. Ensuring that you only store necessary and high-quality data can help control these costs.

💡 Tip: Regularly review and clean your datasets to avoid storing redundant or outdated data, thus keeping storage costs manageable.

Monitoring and Managing Costs

To keep your expenses in check, PropulsionAI provides a detailed billing section where you can monitor your balance, view your usage history, and add funds as needed. Here are some strategies for managing costs:

• Choose Appropriate Hardware: Balance your need for performance with your budget by selecting hardware that aligns with your project requirements.

• Monitor Usage: Keep an eye on your training and deployment durations to avoid unnecessary costs.

• Leverage Free Features During Beta: Take advantage of the Knowledge Base while it’s free, and use this time to plan how you’ll manage these costs once charges are implemented.

Understanding these cost factors will allow you to better plan and manage your AI projects, ensuring that you get the most value from PropulsionAI while staying within budget.