How to Build an RFP Response Agent

May 1, 2025

Kevin Bartley

Customer Success at Stack AI

RFPs are typically answered by sales, business development, or proposal teams within companies that offer the products or services being requested. These teams often collaborate with subject matter experts, project managers, finance, legal, and marketing departments to craft a comprehensive response that meets the RFP requirements. 

However, this process is time-consuming and complicated, and can lead to missed opportunities. But with the advent of AI agents, teams can now answer RFPs automatically in seconds rather than days.

In the following blog, we’ll show you how to build an RFP response agent, and detail its benefits for teams across industries.   

What is an RFP? 

A Request for Proposal (RFP) is a formal document that organizations use to solicit bids from potential vendors or service providers for a specific project or service. It outlines the project's requirements, scope, timeline, and evaluation criteria, providing a structured way for companies to submit their proposals. RFPs are commonly used in both the public and private sectors to ensure transparency, competition, and alignment between the buyer’s needs and the vendor’s capabilities.

RFPs are important because they help organizations identify the most qualified and cost-effective partner for a given task, reducing risks and improving project outcomes. By clearly communicating expectations and selection standards, RFPs promote fairness and objectivity in the decision-making process. 

They also encourage vendors to tailor their proposals to the specific goals of the project, which increases the likelihood of finding a strong match between the organization's needs and the solutions offered.

Why Use an AI Agent for RFPs? 

Someone might use an AI agent to respond to an RFP to save time, improve accuracy, and increase the quality and consistency of their proposals. AI can quickly analyze the RFP document, extract key requirements, and generate relevant content based on past proposals, templates, or a company’s knowledge base. This reduces the manual effort required to start from scratch and ensures that critical elements aren't overlooked.

AI agents can also help tailor responses to specific RFP criteria by identifying the most relevant case studies, product features, or qualifications to include. This level of customization, combined with speed and automation, allows teams to respond to more RFPs without sacrificing quality. Additionally, AI can flag inconsistencies, suggest improvements, and even predict how closely a proposal aligns with the issuer’s needs—giving responders a strategic edge.

AI Agent Overview: RFP Response Agent

Industry

Horizontal

Persona

Proposal Team

Problem

Analyzing RFPs, and responding to them, is a very time-consuming task. This limits the number of RFPs a non-profit can respond to.

Solution

The AI agent automatically writes a proposal for the RFP proposal that the user uploads. 

User Interface

Form

LLM

OpenAI - GPT-4o Mini

Data Sources

File Upload (RFP), Knowledge Base (Documents)

Actions

  1. User uploads RFP. 

  2. RFP is summarized by Summarizer.

  3. LLM analyzes RFP alongside document Knowledge Base. 

Time to Launch

Easy

Benefits

  • Respond to RFPs in 15 minutes as opposed to several hours.

  • Eliminate the need to read dense RFPs; automate the process instead.

  • Respond to more RFPs and land more profitable projects. 

Agent Workflow

How to Build RFP Response Agent

Here’s how to build the investment memo AI agent. First, make sure to sign up for a free Stack AI account

Navigate to the account dashboard. Click ‘New Project’.

Click the ‘Workflow Builder’ option.

From here, choose the RFP Response Agent template. 

The launched workflow for the AI agent will look like the image below.

Let’s take a look at each component of the AI agent. First, consider the file upload. This allows the user to upload an RFP for analysis.

The Summarizer node summarizes the RFP uploaded by the user. This makes the RFP more efficient for the LLM. 

There’s also a Knowledge Base node that offers relevant context for the AI agent. These are documents that the LLM can search for contextual information. 

The LLM is OpenAI - GPT-4o mini, which has instructions to receive the summarized text, and write an RFP proposal for it.

Finally, there’s an output node that displays the RFP response so the user can download it or make a copy. 

Now go to the Export tab.

Give your AI agent a name and a description. You can also change the UI in the drop down box.

Now launch the web app and start using your RFP Response Agent! 

This lets you submit more RFPs, much faster, so you can drive more business to your organization.

Launch RFP Response Agent in Stack AI! 

RFPs take an inordinate amount of time to respond to, and they waste the resources of your team. But with the AI agent outlined in this blog, you can automatically respond to RFPs, in seconds instead of days.

And the best part is that that AI agent is already built for you. Simply launch the template directly from the Stack AI dashboard.

Sign up for a free Stack AI account to start using the pre-built AI agent right now. 

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