RFI Response Generator Agent

Corey Solivan

• Oct 27, 2025
• 4 min read

Updated: Nov 3, 2025

The RFI Generator Agent transforms scattered GovCon data—RFIs, SOWs, case studies, and strategies—into compliant, evidence-backed, and mission-aligned response packages.

Data Room AI Launches “RFI Generator Agent” — AI That Writes With Proof, Not Promises

Naples, FL — October 27, 2025 – Data Room AI (DRAI) today announced the launch of the RFI Generator Agent, a guided AI system that helps government contractors transform intelligence into mission-aligned, compliant, and differentiator-rich RFI responses.

The RFI Generator bridges the gap between scattered corporate assets and submission-ready deliverables—empowering capture and proposal teams to respond with confidence, precision, and proof.

“Most RFI tools write first and think later,” said Corey Solivan, Founder & CEO of Data Room AI.“The RFI Generator does the opposite. It listens, learns, aligns, and only then writes—anchored in truth, strategy, and mission context.”

Purpose: Mission-Aligned. Scope-Driven. Research-Supported. No Drift.

The RFI Generator Agent was built for capture, proposal, and strategy teams who need to produce compliant, compelling, and auditable RFI responses—fast, but without sacrificing accuracy or brand integrity.

It consolidates and integrates:

• RFI documents, SOWs, and PWSs
• Customer dossiers (missions, leadership, goals, priorities)
• Corporate strategies (CAMs, win themes, differentiators)
• Case studies, proof points, and past performance
• NAICS codes and contract vehicle data

The result: a mapped, section-by-section RFI response, where every answer is linked to evidence, regulatory codes, and mission context.

The Mission

To redefine RFI response creation as a strategic, evidence-based process that reflects:

✅ Mission Alignment – Speaks the agency’s language and intent

✅ Evidence-Based Differentiation – Backed by real proof

✅ NAICS & Vehicle Readiness – Cross-validated through live checks

✅ Zero Drift – Every statement traceable, no filler or assumptions

How It Works:

• Guided Intake & Comprehension

The RFI Generator begins by guiding users through structured uploads, including solicitation files, customer dossiers, strategy decks, case studies, and proof materials.

After each upload, it summarizes what it learned — allowing users to verify accuracy before it begins drafting.

Example: “From your uploaded DHS Dossier, I’ve identified three mission imperatives: cyber resilience, zero-trust readiness, and data interoperability. Shall I foreground these in the

Executive Summary?”

• File Validation & Scope Mapping

The agent then lists received materials and highlights gaps with a simple checklist: ✅ Confirm / 📁 Upload / ❌ Not Applicable. It extracts:

• Scope keywords (e.g., Cybersecurity Operations, Cloud Migration, Mission Support)
• Technical context and NAICS patterns
• Potential contract vehicle matches (GWACs, IDIQs, BPAs) via live validation
• Precision Crosswalks

Each RFI section is mapped to corporate assets using a dynamic Requirements Crosswalk Table:

RFI Section

Win Themes / CAMs

Case Studies

NAICS / Vehicle

Differentiators

Mission Understanding

“Cyber as a Shared Responsibility”

AFMC Cyber Pilot

541512 / CIO-SP4

Zero-trust deployment record

Technical Capability

“Proven FedRAMP Journey”

DoD Cloud Migration

541513 / GSA MAS

CloudOps framework (DRAI Edge)

Past Performance

“Continuous Readiness”

FEMA AI Proof

541519 / SEWP V

Data governance automation

This table ensures every response is aligned with real-world data, not boilerplate language.

• Response / Supporting Info Split

Each section is output in two formats: Submission Response (for RFI) and Supporting Info (for internal use).

Example:

RFI Response (Submission)

DRAI Commercial aligns directly with the agency’s cloud-first and zero-trust mandates through demonstrated success under the DoD CloudOps modernization initiative. Our solutions leverage FedRAMP-authorized frameworks to ensure compliance, scalability, and mission assurance.

Supporting Info (Internal)

Source: DoD CloudOps Case Study, 2024CAM: “Accelerate Mission Readiness through Secure Automation ”Vehicle: CIO-SP4, GSA MAS (541513)Differentiator: FEMA AI Pilot–validated orchestration logic

This dual-output structure enforces discipline and transparency in every submission.

• Compliance, Proof, and Integrity

Every statement is backed by verifiable data — from case studies, public records, or customer sources.

• No fabricated claims
• No placeholders
• No “TBD” entries

When data is missing, the agent flags: “Not publicly available as of October 2025 — recommend FOIA or agency inquiry.”

Tone and language remain consistent with DRAI’s hallmark: fact-backed, mission-aligned, and auditor-ready.

• User-in-the-Loop Collaboration

Nothing is generated without user approval. At every phase:

• The agent proposes the next step
• The user reviews and edits or confirms to proceed
• Only then does drafting proceed

“Think of it like an AI co-pilot that asks permission before touching the controls,” added Solivan.

• Deliverables

Deliverable

Description

📄 Submission-Ready Volume

Complete RFI response with cover letter & TOC

📘 Supporting Info Appendix

Mappings, sources, NAICS, and vehicle validation

📋 Compliance Checklist

Section-by-section verification summary

Example Output Snapshot

Executive Summary Excerpt:

Our mission alignment with DHS is demonstrated through ongoing engagements under FEMA’s Predictive Response initiative and our proven ability to translate zero-trust principles into operational resilience.

Mapping Example:

RFI Question

Mission Link

CAM

Case Study

Vehicle Eligibility

Describe your cybersecurity modernization experience.

DHS Zero Trust Strategy 2025

CAM-01 “Assured Access”

FEMA AI Pilot

GSA MAS, CIO-SP4

Ideal Users

Role

Benefit

Capture Managers

Create RFI respo