About this Agent

The Corporate Policy Compliance Agent is an AI digital worker designed to ensure that all financial activities within an organization adhere to established internal corporate policies. It continuously monitors transactions and processes, automatically identifying and flagging any deviations or non-compliant actions for further review. This helps organizations maintain compliance, reduce the risk of policy violations, and streamline their internal auditing processes.

Accuracy
TBD

Speed
TBD

Input Data Set

Sample of data set required for Corporate Policy Compliance Agent:

Corporate Policy Compliance

Compliance Check Criteria:

- Authorization limits: Verifies whether expense amounts fall within approved limits for different expense types.

- Expense categories: Ensures expenses are categorized correctly (e.g., Travel, Meals, Software Purchases, etc.).

- Approval workflow: Checks if the necessary approvals were obtained.

- Transaction documentation: Ensures all required documentation (e.g., receipts) is attached.

TransactionID	EmployeeName	Department	ExpenseType	Amount	ApprovalStatus	TransactionDate	PolicyRule
1001	Emily Johnson	Marketing	Travel	2500.0	Approved	2024-09-12	MaxTravelExpense
1002	John Smith	Sales	Meals	450.0	Approved	2024-09-15	MaxMealExpense
1003	Sarah Miller	Finance	Software Purchase	10000.0	Approved	2024-09-20	AuthorizationLimit
1004	Robert Brown	IT	Equipment Purchase	15000.0	Approved	2024-09-22	MaxPurchaseLimit
1005	Jessica Davis	HR	Training	800.0	Approved	2024-09-25	MaxTrainingExpense

Deliverable Example

Sample output delivered by the Corporate Policy Compliance Agent:

TransactionID	EmployeeName	Department	ExpenseType	Amount	TransactionDate	DeviationReason
1001	Emily Johnson	Marketing	Travel	2500.0	2024-09-12	Exceeds Max Travel Expense ($2000 Limit)
1003	Sarah Miller	Finance	Software Purchase	10000.0	2024-09-20	Exceeds Authorization Limit ($5000 Limit)
1004	Robert Brown	IT	Equipment Purchase	15000.0	2024-09-22	Exceeds Max Purchase Limit ($12000 Limit)

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.

Corporate Policy Compliance Agent

About this Agent

Input Data Set

Corporate Policy Compliance

Compliance Check Criteria:

Deliverable Example

Company

Product

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