Back office ops · Production

Field Aerospace cuts proposal drafting from two weeks to 25 minutes with self-hosted n8n

The problem

Field Aerospace's proposal team spent up to two weeks with three to four people per response on government solicitations that often exceed 50 pages, and sometimes learned of relevant opportunities too late to prepare competitive responses, while paying for multiple third-party tools that still failed to meet their needs.

First attempt

Multiple paid third-party tools did not fully meet Field's needs for a secure, self-hosted solution capable of reducing manual effort and enabling earlier opportunity engagement.

Workflow diagram · grounded in source
1
Solicitation upload and trigger
trigger
“Users upload solicitation files, trigger workflows via webhooks, receive notifications when processing completes, and review outputs through a clean interface without interacting directly with workflows”
2
Solicitation decomposition
ai_action
“n8n orchestrates a set of workflows that break each solicitation into structured sections, extract key prompts and requirement language, and generate draft responses”
3
Reference-grounded draft generation
ai_action
“The system combines solicitation content with an internal library of approved reference material, including past performance examples, so outputs reflect Field's real capabilities rather than generic AI text. Drafts are returned in Markd…”
4
Draft export to Microsoft Teams
output
“exported into Microsoft Teams for review and refinement”
5
Requirements matrix extraction
ai_action
“Field built a workflow that processes long solicitation documents and produces a consolidated requirements matrix. Instead of manually searching for shall, must, and will statements, teams receive a structured output they can validate an…”
6
Daily solicitation retrieval
integration
“Field implemented an automated evaluator workflow on n8n that connects to Deltek GovWin via API. Each day, n8n retrieves newly created or updated solicitations”
7
Opportunity scoring and report delivery
routing
“n8n retrieves newly created or updated solicitations, scores them against Field's internal criteria, and delivers a filtered report to business development and leadership”
Reported outcome

Field replaced two legacy tools and eliminated approximately $30,000 in annual software costs.
Proposal drafts now reach an 80% starting point in roughly 25 minutes rather than two weeks, and requirements extraction now takes 15 to 20 minutes instead of hours.

Reported metrics
Annual software cost savings$30,000
Proposal draft time to 80% stageroughly 25 minutes
Requirements extraction time15 to 20 minutes
Proposal starting point completeness80%
Show all 5 reported metrics
annual software cost savings$30,000
proposal draft time to 80% stageroughly 25 minutes
requirements extraction time15 to 20 minutes
proposal starting point completeness80%
legacy tools replacedtwo
Reported stack
n8nReactNode.jsMicrosoft TeamsDeltek GovWin
Source
https://n8n.io/case-studies/field-aerospace/
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Field replaced two legacy tools and eliminated approximately $30,000 in annual software costs.

What tools did this team use?

n8n, React, Node.js, Microsoft Teams, Deltek GovWin.

What results were reported?

Annual software cost savings: $30,000; Proposal draft time to 80% stage: roughly 25 minutes; Requirements extraction time: 15 to 20 minutes; Proposal starting point completeness: 80% (source-reported, not independently verified).

What failed first in this deployment?

Multiple paid third-party tools did not fully meet Field's needs for a secure, self-hosted solution capable of reducing manual effort and enabling earlier opportunity engagement.

How is this back office ops AI workflow structured?

Solicitation upload and trigger → Solicitation decomposition → Reference-grounded draft generation → Draft export to Microsoft Teams → Requirements matrix extraction → Daily solicitation retrieval → Opportunity scoring and report delivery.

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