RFI Automation: Faster, Consistent Responses in 2025

The first time a major prospect sent us an RFI, I thought we were ready. We had case studies, past proposals, and plenty of client wins to draw from. But when the deadline came, the reality looked very different. Our team was buried in Google Drive folders, copy-pasting old answers, rewriting entire sections, and formatting until midnight. What should have been a moment of confidence turned into a four-to-five-hour scramble that left us drained and distracted from real client work.

And it was not just that one RFI. Every new request felt the same. The stakes were high, yet the process was messy and inconsistent. Instead of showing up as the best version of ourselves, we were stuck in repetitive admin work. That was my wake-up call. We did not have a writing problem. We had a knowledge problem.

The Problem with Traditional RFI Responses

Our old process was slow and inconsistent. When a company sent an RFI, we would dig through Google Drive for past responses, copy-paste snippets, reword them for the new client, and spend hours formatting the document. If the question was new, we had to create an answer from scratch, which took even more time. The result was hours or even days of work with little consistency across responses. It became clear we needed a smarter way to use the knowledge we already had of our case studies, proposals, and past RFIs without starting over each time.

Why Tools Alone Failed and What Actually Worked

At first, it seemed simple to lean on ChatGPT or another LLM, but that approach quickly fell short. A generic model did not understand our business, and drafting from scratch only produced inconsistent results. Even when the output looked useful, we still had to spend hours fact-checking, formatting, and aligning it with our past work.

The real turning point was realizing that RFIs were not a writing problem at all. They were a knowledge problem. We already had case studies, past responses, proposals, and testimonials, but they were scattered across folders and hard to reuse. The solution was to centralize everything into a knowledge base that updated automatically. Every time a new RFI or case study was added, the system became smarter. So when the next RFI arrived, the system could pull directly from our own validated knowledge and generate a polished, ready-to-send document in minutes. That was the true “aha” moment.

The New Process: How RFI Automation Works

Let me walk you through the workflow step by step.

Step 1: Building the Knowledge Base

We began by consolidating all past content. Case studies were organized into one knowledge base, and 336 pages of RFI responses into another. Every new case study or RFI response is automatically added, ensuring the system stays updated and never relies on outdated content.

Step 2: Analyzing the New RFI

When a new RFI arrives, we upload the PDF or paste the URL. The system extracts all questions and requirements, organizes them, and highlights what the client is asking for such as engagement models, scope, or team details. This gives us a clear, structured view without the need to scan long documents manually.

Step 3. Generating the Response with Context

This is the stage where the real value shows up. The system brings together three important inputs and feeds them into the LLM. First, it uses the RFI document itself, which contains the client’s questions and requirements. Next, it pulls from our case study knowledge base, which highlights relevant past work, client testimonials, and measurable results. Finally, it uses our RFI response knowledge base, a collection of answers we have already crafted and refined over time. Using these three sources, the LLM generates a new response that is customized to the client’s needs. The result is not a generic AI answer. Instead, it is rooted in our actual work, aligned with our past messaging, and written in a way we already know resonates with clients.

Step 4. Formatting into a Client-Ready Document

Once the draft is done, the system instantly formats it into a polished Google Doc. It adds clear headings, dividers, proper naming, and clean formatting that’s easy to share. What used to take hours now takes just a couple of minutes.

Step 5. Handling “Out-of-Syllabus” Questions

When a client asks something we haven’t covered before, the system marks it in red. We then create a new response, add it to the knowledge base, and ensure it is ready for future RFIs. This way, the system keeps improving with every new question.

Real Benefits We’ve Seen

• Time saved: Tasks that took hours now finish in under 2 minutes.
  
• Consistency: Every response meets the same high standard.
  
• Scalability: The system grows stronger as we handle more RFIs.
  
• Cost savings: Runs smoothly on free LLMs like Google Gemini, no need for paid tools.

For me as a founder, the biggest benefit is peace of mind. The team is free from repetitive admin work and can focus on strategy, while the system takes care of drafting. We’re also building the next step: a setup where pasting an RFI link instantly generates a response.

Key Takeaways for B2B SaaS Teams

If you’re reading this as a SaaS marketer or GTM lead, here’s what I’d want you to take away:

1. Treat RFIs as a knowledge management problem, not a writing problem.
   Your past case studies and responses are gold. Don’t let them sit in random folders. Centralize and structure them.
   
2. Automate the repetitive 80%, focus on the strategic 20%.
   You’ll still need to review and handle edge cases, but automation can cover the bulk of the work.
   
3. Start simple, scale later.
   We didn’t need fancy custom GPTs or expensive tools. A structured knowledge base + free LLM + smart formatting was enough to change our workflow.
   
4. Build a feedback loop.
   Every new question should feed back into the knowledge base. Over time, your system becomes smarter than any single team member.

Final Thoughts

Automating RFI responses wasn’t just about saving time. It gave us leverage. Every hour we free up from repetitive work is time we can spend on strategy, creative campaigns, and delivering results for clients. The system is still improving, but the benefits are already clear: faster responses, less stress, and more consistency. If your team is still drafting RFIs manually, rethink the process. Build a knowledge base, automate the repeatable parts, and keep humans for the exceptions. That’s how you scale without burning out.

Want to automate your RFI responses?

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We built this system to cut response time from half a day to under two minutes while keeping every answer consistent and client-ready. If you’re exploring automation for your GTM or sales process, feel free to reach out or connect with me on LinkedIn. Always happy to share what worked for us and how you can adapt it to your team.

— Karthick Raajha
Founder, Revv Growth

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