Real Agent Cases

Draft government-solicitation proposals in 25 minutes with n8n AI workflows

Posted
by Field Aerospace / n8n (Shawn Tatum)
Last checked
Method:
How we verify

Evidence: Company case studyA write-up published by the company that makes the agent or uses it.

Outcome

According to n8n's case study, Field Aerospace's self-hosted n8n AI workflows bring a proposal draft that used to take about two weeks of work from three or four people to an 80% starting point in roughly 25 minutes, and replaced two legacy tools, eliminating approximately $30,000 in annual software costs (the case study's headline gives $22,000 a year).

According to n8n:Proposal time cut from 2 weeks to 25 minutes

This is the source's own number. We haven't measured it.

Agent

n8n (AI-powered workflows)

Prompt Recreated prompt

The source didn't share its exact prompt, so we wrote this from what it describes.

Ingest this government solicitation, extract requirements into a matrix, and draft proposal responses using our approved past-performance library; export a Markdown draft marked as AI-generated for Teams review.

Try this in:

ChatGPT Gemini Grok

Sends the Recreated prompt shown above. ChatGPT and Grok open with it filled in, and ChatGPT may send it straight away. Gemini opens empty, so we copy the prompt for you to paste. Every button also copies it.

The source used n8n (AI-powered workflows), which can take actions in a browser or app. These are general chat tools, so results may differ, and a normal chat may only give you a plan.

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These links are only a shortcut. We're not affiliated with OpenAI, Google or xAI, and your results may not match the source.

Optional stronger version

Our rewrite with extra checks. The poster didn't test it.

Goal: Turn a government solicitation into a requirements matrix and a draft response from our approved past-performance library.

Inputs (fill in or confirm):
- Solicitation documents
- Past-performance library
- Response format and page limits
- Due date

Rules:
- Extract every 'shall' and evaluation criterion into a numbered matrix with section references.
- Map each requirement to library content; mark gaps.
- Draft responses using only approved library text and facts.
- Label the draft clearly as AI-generated for review.
- Extract every requirement into a compliance matrix before drafting.
- Map each requirement to a section of the proposal.
- Only use past performance that's in the library; never invent projects or numbers.
- Flag requirements we can't meet.
- Never submit; I'll review and submit.

Checkpoint: Don't submit or send anything outside the review channel.

If you get stuck: If a requirement is ambiguous, list it as a question for the contracting officer. If a login, CAPTCHA or two-step code appears, stop and ask me to handle it; never guess or store passwords.

Verify before you finish: Check every requirement in the matrix has a response or a gap note.

Output: Requirements matrix, Markdown draft and gap list.

Done when: reviewers get a complete matrix and an ~80% draft to edit.

Source

https://n8n.io/case-studies/field-aerospace/

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