Categorization Agent

About the Agent

The Categorization Agent uses generative AI to automatically categorize customer feedback into predefined categories such as product quality, delivery issues, and support experience. This eliminates manual sorting, freeing customer service teams to focus on direct customer interaction and problem-solving. The agent's accurate categorization provides reliable insights, enabling faster responses to customer concerns and more effective resource allocation. By tracking trends and identifying areas needing immediate attention, businesses can make data-driven decisions to improve products, services, and the overall customer experience. This streamlined feedback analysis empowers companies to proactively address customer needs, ultimately fostering stronger customer relationships, increasing loyalty, and driving business growth.

Accuracy
TBD

Speed
TBD

Input Data Set

Sample of data set required for Categorization Agent:

Categorization Agent input

Customer Name	Feedback Date	Feedback Text
Nathen Smith	10/10/2024	The product arrived late and was damaged.
Emily Johnson	10/9/2024	Customer support was very helpful in resolving my issue.
David Brown	10/8/2024	Quality of the product is not up to the mark.
Sarah Williams	10/7/2024	Delivery was quick and the packaging was excellent.
Michael Lee	10/6/2024	Had trouble getting help from customer support.
Laura Martinez	10/5/2024	The product was missing some parts upon arrival.
James Carter	10/4/2024	Excellent service, but the product broke within a week.
Patricia Miller	10/3/2024	Customer support was unresponsive for hours.
Andrew Wilson	10/2/2024	I love the product, but the instructions were unclear.

Deliverable Example

Sample output delivered by the Categorization Agent:

Customer Name	Feedback Date	Feedback Text	Category
Nathen Smith	10/10/2024	The product arrived late and was damaged.	Delivery Issues
Emily Johnson	10/9/2024	Customer support was very helpful in resolving my issue.	Support Experience
David Brown	10/8/2024	Quality of the product is not up to the mark.	Product Quality
Sarah Williams	10/7/2024	Delivery was quick and the packaging was excellent.	Delivery Experience
Michael Lee	10/6/2024	Had trouble getting help from customer support.	Support Experience
Laura Martinez	10/5/2024	The product was missing some parts upon arrival.	Product Issues
James Carter	10/4/2024	Excellent service, but the product broke within a week.	Product Quality
Patricia Miller	10/3/2024	Customer support was unresponsive for hours.	Support Experience
Andrew Wilson	10/2/2024	I love the product, but the instructions were unclear.	Product Documentation

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.

Categorization Agent

About the Agent

Input Data Set

Deliverable Example

Company

Product

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