AI Agent for RFP & Proposal Automation

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AI Case Study

You just got a 78-page RFP.
Deadline: 48 hours

Monday, 9:42 AM

You open the document

Scroll… Scroll… Scroll…

Half the answers already exist somewhere in your company.
You just don’t know where.

❌ Today
  • Days of writing
  • Endless copy-paste
  • Constant expert follow-ups
✅ With AI Agent
  • Draft in minutes
  • Auto-filled responses
  • Ready for review
Role: Product Designer Duration: 6 weeks Type: AI Product

0

Time Reduction

3x

Faster Drafting

Expert Dependency

RFPs aren’t a writing problem
They’re a knowledge retrieval problem

My Role

  • Led UX design for AI workflows
  • Defined system interaction patterns
  • Designed and built frontend prototype

A typical RFP day

9:00 AM RFP received

10:30 AM Searching past responses

1:00 PM Waiting for expert input

4:00 PM Still drafting

Next day Reviewing & fixing inconsistencies

Where time was spent

🔍 Searching content — 40%
✍️ Writing responses — 30%
📩 Expert coordination — 20%
🔄 Rework — 10%

The Problem

Teams weren’t creating new answers—they were searching, copying, and rewriting existing ones. This made proposal creation slow, repetitive, and heavily dependent on domain experts.

Time Intensive

4–6 hours per proposal

Knowledge Dependency

Experts repeatedly involved

Inconsistency

No standardized responses

Key Insight

80% of RFP responses were repetitive and existed within internal documents. The challenge wasn’t writing — it was retrieving and structuring knowledge efficiently.

Solution

Designed an AI-powered agent that retrieves internal knowledge and generates structured, context-aware RFP responses, significantly reducing manual effort.

What if this was all it took?

🗎 Upload RFP

⚙️ AI parses + retrieves knowledge

✨ Draft generated in minutes

Designing the AI System

Knowledge Layer

Structured internal documents for retrieval

AI Layer

Generates contextual responses using prompts

User Layer

Review, edit, and approve outputs

Workflow Transformation

Before

Sales → Expert → Draft → Review → Submit

After

Sales → AI Agent → Review → Submit

Designing for AI Constraints

Building AI-driven products requires balancing automation with user trust, accuracy, and control.

Handling Hallucinations

Designed structured input and knowledge retrieval to minimize incorrect or fabricated responses.

Accuracy First

Trust & Transparency

Clearly indicated AI-generated content and allowed users to understand source context.

User Trust

User Control

Enabled users to edit, refine, and override AI outputs to ensure reliability in critical workflows.

Human in Loop

Editable Flows

Designed flexible workflows where users can review, modify, and finalize responses before submission.

Flexibility

Key Design Decisions

Transparency

Users can see and edit AI-generated responses

Control

Manual override for critical responses

Accuracy

Structured inputs reduce hallucinations

Final Design

Intro Page

Wireframe
AI-Powered Document Generation

Generate structured documents automatically using AI-driven prompts and templates.

Search Workflow and Templates

Configure and manage reusable search workflows and document templates.

RFP Search Using Predefined Prompts

Quickly find relevant RFPs using standardized, ready-to-use AI prompts.

Test Lab / Prompt Engineering

Wireframe
Create Predefined Prompts

Design reusable prompts to ensure consistent and efficient content generation.

Prompt Details & Configuration

Define prompt behavior, scope, and parameters for accurate AI outputs.

Advanced Prompt Configuration

Fine-tune AI responses using advanced rules and control settings.

Template Management

Wireframe
Template Creation

Build structured templates to standardize document generation

Template Details Setup

Configure metadata, naming, and ownership details for templates

Add Sections to Template

Dynamically create and customize sections within a template

Generate Content

Wireframe
Template Configuration & Rules

Control template behavior, permissions, and generation logic

AI Content Generation

Generate high-quality content automatically using AI models

Confidence Score Assignment

Assign AI-generated confidence levels to validate output reliability

Request Management

Wireframe
Rich Text Editor (RTE) for Content

Edit and refine generated content using a powerful rich text editor

Current Request Dashboard

View and track all ongoing and completed content generation requests

Uploaded Files Repository

Access and manage all files uploaded for document generation

Impact

🙍‍♂️ User Testing Participants

  • 6 Business Analysts
  • 5 Administrative Staff
  • 4 Software Developers

📝 Tasks to complete using AI

  • Generate a professional invoice from a template
  • Customize a report using the document builder
  • Export documents in PDF, DOCX, and Markdown formats
  • Use AI-assisted content generation to populate sections
  • Reduced dependency on subject matter experts by 40%

📶 Statistics to analyze AI

  • Success rate
  • User satisfaction
  • Average generation time
  • Ease of use (SUS score)

🎢 Quick Insights

  • Document export is fast and reliable
  • Love the AI suggestions—it saves time
  • AI sometimes adds irrelevant content
  • Reduced proposal drafting time by ~60%

Key Learnings

  • AI UX requires balancing automation with trust
  • Structured knowledge is critical for accuracy
  • User control is essential in AI-driven workflows

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