Agents-internal

About this Agent

The Procurement Budget Allocation Agent is an AI-driven solution designed to automate the allocation of budgets for procurement projects. By analyzing project scopes, vendor proposals, and departmental needs, this digital worker ensures optimal resource distribution, enhancing efficiency and decision-making in procurement processes.

Accuracy
TBD

Speed
TBD

Input Data Set

Sample of data set required for Procurement Budget Allocation Agent:

Procurement budget

Project_Name	Department	Project_Scope	Vendor_Proposal_Amount	Department_Needs
Office Renovation	Facilities	Full renovation of office	150000	100000
New IT Infrastructure	IT	Upgrade of IT systems and network	200000	250000
Marketing Campaign	Marketing	New marketing strategy	50000	60000
R&D Initiative	R&D	Development of new product	300000	280000
Supply Chain Improvement	Operations	Streamline supply chain processes	120000	130000

Deliverable Example

Sample output delivered by the Procurement Budget Allocation Agent:

Project_Name	Allocated_Budget	Budget_Status
Office Renovation	130000	Approved
New IT Infrastructure	220000	Approved
Marketing Campaign	55000	Adjusted
R&D Initiative	290000	Approved
Supply Chain Improvement	125000	Adjusted

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.

Procurement Budget Allocation Agent

About this Agent

Input Data Set

Deliverable Example

Company

Product

Contact us

Get more information

In this personalized demo, you will:

Explore ZBrain Platform

Discover Workflow Integrations

Engage in Q&A Session