Agents-internal

About this Agent

The Contract Compliance Review Agent is a specialized AI digital worker designed to meticulously review financial contracts, ensuring they adhere to both internal policies and external regulations. This AI agent scrutinizes contract details to identify any discrepancies or potential compliance issues, flagging them for correction. It streamlines the compliance review process, reducing the risk of non-compliance and enhancing the integrity of financial operations.

Accuracy
TBD

Speed
TBD

Input Data Set

Sample of data set required for Contract Compliance Review Agent:

Financial contracts input

Contract_ID	Party_A_Name	Party_B_Name	Contract_Amount	Contract_Date	Contract_Termination_Date	Governing_Law	Clauses_Dispute_Resolution	Clauses_Compliance	Payment_Terms	Penalty_Clauses	Notes
C001	John Harrison	Global Corp Ltd	$500,000	2024-01-15	2026-01-15	New York	Arbitration	GDPR, SOX	Net 30	2% per week	Pending legal approval
C002	Sarah Johnson	BlueSky Partners	$750,000	2023-10-01	2024-10-01	California	Mediation	SOX	Net 45	5% of contract	Review for termination clause
C003	David Miller	Innovate LLC	£400,000	2024-02-28	2027-02-28	London	Court Litigation	GDPR, SOX	Net 60	None	Check GDPR compliance
C004	Amanda Thompson	Horizon Services	£200,000	2022-06-01	2025-06-01	Birmingham	Arbitration	SOX	Net 30	3% per month	Possible breach of payment terms

Deliverable Example

Sample output delivered by the Contract Compliance Review Agent:

Contract_ID	Party_A_Name	Compliance_Status	Issues_Flagged	Recommended_Actions	Last_Reviewed_By	Last_Reviewed_Date
C001	John Harrison	Non-compliant	Missing GDPR compliance, legal approval pending	Add GDPR clause, finalize legal approval	Emily Watson	2024-10-10
C002	Sarah Johnson	Compliant	None	No actions needed	Thomas Bennett	2024-10-12
C003	David Miller	Non-compliant	Missing SOX compliance	Review SOX clause and update contract	Laura Anderson	2024-10-11
C004	Amanda Thompson	Compliant	None	No actions needed	Robert Matthews	2024-10-13

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.

Contract Compliance Review Agent

About this Agent

Input Data Set

Deliverable Example

Company

Product

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