Agents-internal

About this Agent

The Withholding Tax Monitoring Agent is a specialized AI digital worker designed to ensure comprehensive compliance with withholding tax obligations. This intelligent agent meticulously monitors financial transactions to guarantee that all necessary tax deductions are made accurately and reported in a timely manner. By automating the process of withholding tax compliance, the agent reduces the risk of errors and penalties, providing peace of mind and efficiency to the finance department.

Accuracy
TBD

Speed
TBD

Input Data Set

Sample of data set required for Withholding Tax Monitoring Agent:

Employee Withholding Data

Employee_ID	Employee_Name	Gross_Pay	Withholding_Tax_Rate	State	Federal_Tax_Withheld	State_Tax_Withheld	Pay_Date
101	John Smith	6500	15%	California	975	650	2024-09-30
102	Emma Johnson	5800	12%	New York	696	696	2024-09-30
103	William Brown	7200	14%	Texas	1008	0	2024-09-30
104	Olivia Williams	6000	10%	Florida	600	0	2024-09-30
105	James Davis	5500	18%	Georgia	990	495	2024-09-30

Deliverable Example

Sample output delivered by the Withholding Tax Monitoring Agent:

Employee_ID	Employee_Name	Gross_Pay	Expected_Federal_Tax	Actual_Federal_Tax	Expected_State_Tax	Actual_State_Tax	Status	Comment
101	John Smith	6500	975	975	650	650	Compliant	No discrepancies found
102	Emma Johnson	5800	696	696	696	696	Compliant	No discrepancies found
103	William Brown	7200	1008	1008	0	0	Compliant	No state tax in Texas
104	Olivia Williams	6000	600	600	0	0	Compliant	No state tax in Florida
105	James Davis	5500	990	990	495	495	Compliant	No discrepancies found

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.

Withholding Tax Monitoring Agent

About this Agent

Input Data Set

Deliverable Example

Company

Product

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