Generative AI Applications Archives

AI for accounts payable and receivable

by ZBrain | Mar 26, 2025 | Generative AI, Generative AI Applications, Generative AI Use Cases

← All Insights AI in accounts payable and receivable: Scope, integration, use cases, challenges and trends Listen to the article Your browser does not support the audio element. In the financial operations landscape, significant transformations are occurring in...

AI for HR planning and strategy

by ZBrain | Mar 25, 2025 | Generative AI, Generative AI Applications, Generative AI Use Cases

← All Insights AI for HR planning and strategy: Scope, integration, use cases, challenges and future outlook Listen to the article Your browser does not support the audio element. AI is redefining HR planning and strategy, offering solutions to long-standing...

AI in quote management

by ZBrain | Mar 25, 2025 | Generative AI, Generative AI Applications, Generative AI Use Cases

← All Insights AI in quote management: Scope, integration, use cases, challenges and future outlook Listen to the article Your browser does not support the audio element. The quoting process is a critical touchpoint in sales, directly impacting conversion rates,...

Generative AI for sales

by ZBrain | Mar 24, 2025 | Generative AI, Generative AI Applications, Generative AI Use Cases

← All Insights Generative AI in sales: Scope, adoption, use cases, challenges, considerations and trends Listen to the article Your browser does not support the audio element. Sales has always been about building relationships, creating value for customers and driving...

AI for control and risk management

by ZBrain | Mar 24, 2025 | Generative AI, Generative AI Applications, Generative AI Use Cases

← All Insights AI for control and risk management: Scope, integration, use cases, challenges and future outlook Listen to the article Your browser does not support the audio element. Control and risk management are integral to every organization’s health, encompassing...

AI for plan-to-deliver

by ZBrain | Mar 19, 2025 | Generative AI, Generative AI Applications, Generative AI Use Cases

← All Insights AI for plan-to-deliver (P2D): Scope, integration, use cases, challenges and future outlook Listen to the article Your browser does not support the audio element. The plan-to-deliver (P2D) process is fundamental to supply chain operations, encompassing...

ZBrain credits and their usage

A credit is a unit of usage on ZBrain. Credits are consumed whenever you perform actions such as embedding documents or querying an app. Here’s how credits are utilized:

Document Embedding:

When you upload a document, it is processed and embedded to create a searchable vector representation. This step consumes credits based on the size of the document and the embedding model used.

Input Processing:

When you ask a question, the relevant context is retrieved from the embeddings and processed by the Large Language Model (LLM). This step incurs a credit cost based on the model and the number of input tokens.

Generating Output

The LLM then generates a response based on the processed input, consuming additional credits based on the number of output tokens.

The cost in credits for various models and processes is detailed below:

Models and Credit Consumption:

Model	Input Cost	Output Cost
GPT-4o	2,500 credits / 1M tokens	7,500 credits / 1M tokens
GPT-4	15,000 credits / 1M tokens	30,000 credits / 1M tokens
GPT-4-32k	30,000 credits / 1M tokens	60,000 credits / 1M tokens
GPT-3.5 Turbo	250 credits / 1M tokens	750 credits / 1M tokens

Embedding Models:

Model	Input Cost
text-embedding-3-small	20 credits / 1M tokens
text-embedding-3-large	130 credits / 1M tokens
ada v2	100 credits / 1M tokens

When you create a knowledge base or query an app, credits are deducted based on the embedding, input, and output token usage. This ensures you only pay for what you use while leveraging the full power of advanced AI models.

AI for accounts payable and receivable

AI for HR planning and strategy

AI in quote management

Generative AI for sales

AI for control and risk management

AI for plan-to-deliver

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