👨‍💻FreeAI Model

Goal: Offset the cost of a user's subscription by providing AG token rewards that match, or even exceed the subscription costs

Overview

Aggre's FreeAI aims to offset the cost of user subscriptions with AG token rewards, making access to the best AI models effectively free. This model balances user incentives with platform revenues and expenses, ensuring financial viability.

How it Works

Inputs

1. Paid Subscriptions:

Users subscribe to Aggre, paying a monthly fee to access AI credits from the top AI models.
Different subscription tiers offer varying quantities of AI credits, determining the number of prompts users can submit.

2. User Data Contributions:

Users actively submit prompts and rate the performance of AI models.
These activities generate valuable data that can be packaged and sold as data points.

3. Advertisements:

In-app advertisements displayed to free-tier users.

Outputs

1. Operational Costs:

Routing user prompts through top AI models via API calls.
Infrastructure and other operational expenses

2. AG Token Rewards:

Users earn AG token by rating AI model performance, with dynamic emissions based on current token price and the user's subscription tier.

Achieving Economic Balance

Subscription Revenue vs. AI Credit Costs:

Subscription fees are set higher than the cost of the corresponding AI credits. This ensures that each subscription generates a positive cash flow for the platform.
For example, if a subscription costs $20 per month, the cost of the AI credits provided should be slightly less, ensuring a margin that contributes to overall revenue.

Balancing AG Rewards with Sustainability:

The platform limits the number of prompts a user can submit per month based on their subscription tier, ensuring that AG token emissions are controlled. Once users reach their maximum prompt limit, they can reload their credits, generating additional revenue for the platform.
It is OK for Aggre to run at a -PNL when considering the value of AG token rewards distributed while in a growth oriented trajectory. For example, OpenAI runs at a -$14/month loss per user. Intelligent tokenomics and real yield can offset AG token rewards.

PreviousInitial Supply & Allocations NextSupported Blockchains

Last updated 3 months ago

How it Works

Inputs

1. Paid Subscriptions:

Users subscribe to Aggre, paying a monthly fee to access AI credits from the top AI models.

Different subscription tiers offer varying quantities of AI credits, determining the number of prompts users can submit.

2. User Data Contributions:

Users actively submit prompts and rate the performance of AI models.

These activities generate valuable data that can be packaged and sold as data points.

3. Advertisements:

In-app advertisements displayed to free-tier users.

Outputs

1. Operational Costs:

Routing user prompts through top AI models via API calls.

Infrastructure and other operational expenses

2. AG Token Rewards:

Users earn AG token by rating AI model performance, with dynamic emissions based on current token price and the user's subscription tier.

Achieving Economic Balance

Subscription Revenue vs. AI Credit Costs:

Subscription fees are set higher than the cost of the corresponding AI credits. This ensures that each subscription generates a positive cash flow for the platform.

For example, if a subscription costs $20 per month, the cost of the AI credits provided should be slightly less, ensuring a margin that contributes to overall revenue.

Balancing AG Rewards with Sustainability:

The platform limits the number of prompts a user can submit per month based on their subscription tier, ensuring that AG token emissions are controlled. Once users reach their maximum prompt limit, they can reload their credits, generating additional revenue for the platform.

It is OK for Aggre to run at a -PNL when considering the value of AG token rewards distributed while in a growth oriented trajectory. For example, OpenAI runs at a -$14/month loss per user. Intelligent tokenomics and real yield can offset AG token rewards.