How Field Aerospace uses n8n to draft government proposals in minutes
Field Aerospace, an aircraft modification company, runs a self-hosted n8n deployment behind an internal web app to draft proposal responses, extract requirements and screen government solicitations. As reported by n8n, it cut proposal drafting time and removed two legacy tools.
The problem
Field Aerospace's teams had to answer long, complex government solicitations, many over 50 pages, and a proposal draft took about two weeks from three to four people. Relevant opportunities were sometimes found too late, forcing rushed responses. The company also paid for several third-party tools that did not fully fit, and it needed a solution that could run on premises.
How they did it
- Deploy n8n self-hosted so everything runs on premises.
- Build a React and Node.js web app where staff upload solicitation files and trigger n8n workflows via webhooks.
- Split each solicitation into sections, pull out the prompts and requirement language, and generate draft answers using an internal library of approved reference material and past performance examples.
- Return drafts as Markdown marked as AI-generated and export them to Microsoft Teams for review.
- Add a workflow that builds a requirements matrix from the will/shall/must statements in long documents.
- Run a daily evaluator that pulls new or updated solicitations from Deltek GovWin via API, scores them against internal criteria and sends a filtered report.
Results
- As reported by n8n, a proposal draft reaches about an 80% starting point in roughly 25 minutes, versus about two weeks of work from three or four people before.
- As reported by n8n, requirements extraction now takes 15 to 20 minutes depending on document size, where it used to take hours.
- As reported by n8n, two legacy tools were replaced, eliminating approximately $30,000 in annual software costs.
- The daily opportunity evaluator reduces the risk of missed solicitations and last-minute proposal scrambles.
As reported by the source (n8n customer case study); AgentGid did not measure these figures.
This suits a team with developers who can build and maintain a React/Node front end, run self-hosted n8n on premises, and keep an approved reference library current. The headline figures (80% draft in 25 minutes, about $30,000 saved) are n8n-reported, and each draft still needs human review. If you want a free open-source alternative, Langflow is listed as Free (OSS).
The agent used here
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