Agents-internal

About this Agent

The Compliance Monitoring Agent is an AI digital worker designed to ensure continuous adherence to security policies and regulatory requirements within an organization. This agent actively monitors systems and processes, providing real-time reporting and generating alerts for any deviations from established standards. By automating the compliance monitoring process, it enhances the organization's ability to maintain security integrity and swiftly address potential vulnerabilities or non-compliance issues.

Accuracy
TBD

Speed
TBD

Input Data Set

Sample of data set required for Compliance Monitoring Agent:

Incident report

Incident ID	Incident Type	Severity Level	Source IP	Destination IP	Timestamp	Description
1	Malware	High	192.168.1.10	10.0.0.51	2024-10-11T10:00:00Z	Detected malware on a server.
2	Phishing	Medium	192.168.1.20	10.0.0.43	2024-10-11T10:05:00Z	User reported phishing email.
3	DDoS Attack	High	203.0.113.5	10.0.0.10	2024-10-11T10:10:00Z	DDoS attack on the web server.
4	Unauthorized Access	Critical	192.168.1.30	10.0.0.11	2024-10-11T10:15:00Z	Unauthorized access attempt detected.
5	Data Breach	High	198.51.100.25	10.0.0.19	2024-10-11T10:20:00Z	Potential data breach identified.

Deliverable Example

Sample output delivered by the Compliance Monitoring Agent:

Incident ID	Response Action	Containment Steps	Eradication Steps	Recovery Steps	Follow-Up Actions
1	Quarantine Malware	Isolate affected server	Remove malware using antivirus	Restore from last backup	Notify user and update security policies
2	Alert User	Inform user to avoid suspicious links	No eradication needed	Monitor for further reports	Send training on phishing awareness
3	Implement DDoS Mitigation	Activate DDoS protection services	Analyze attack patterns	Monitor service performance	Review network security measures
4	Block Source IP	Block access from unauthorized source	Audit access logs	Reset affected user credentials	Conduct a full security audit
5	Initiate Investigation	Isolate affected database	Identify and patch vulnerabilities	Monitor for unusual activities	Notify affected parties and regulators

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.

Compliance Monitoring Agent

About this Agent

Input Data Set

Deliverable Example

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