How a Tier-1 U.S. Defense Contractor Built Secure AI Agents for Acquisition and Compliance Workflows

How a Tier-1 U.S. Defense Contractor Built Secure AI Agents for Acquisition and Compliance Workflows

A defense contractor uses on-prem AI agents and self-hosted LLMs to streamline proposals, engineering reviews, and RMF/ATO compliance securely.

Client

Defense Contractor

Challenge

Slow, manual proposal, engineering, and compliance workflows couldn’t be modernized without keeping all data strictly on-premise.

Solution

StackAI enabled fully on-prem AI agents powered by self-hosted LLMs that automated these workflows while meeting all defense security and governance requirements.

Overview

A major U.S.–based defense contractor, one of the largest suppliers of mission-critical systems to the U.S. government, was facing mounting pressure across engineering, capture, and compliance operations. Every program produced thousands of pages of design specs, subsystem descriptions, testing protocols, and regulatory requirements. Teams often spent weeks cross-referencing documents, rewriting boilerplate language, or manually tracing requirements back to government-issued defense guidelines.

These workflows weren’t just slow; they were risky. Missing a single compliance reference in an engineering design review could delay certification. Submitting an incomplete RFP response could disqualify a bid. And generating quarterly compliance packages (such as RMF/ATO documentation) required meticulous mapping of evidence to controls, demanding hundreds of hours from highly specialized staff.

Critically, none of this information could ever leave their secure environment. That ruled out traditional SaaS AI tools and any external processing.

Using StackAI, the contractor built an on-premise AI agent platform running entirely inside their own network, mainly powered by open-source LLMs, that automated their most painful, document-heavy workflows. Over time, these AI agents became a shared layer across engineering, compliance, and business development: consistent, secure, reviewable, and auditable.

60–70% reduction in time to draft large, multi-volume proposals
50–65% faster engineering design compliance reviews
3× increase in RFPs they could credibly respond to
Hundreds of hours saved per compliance package (RMF/ATO)

Engineering Design Compliance Agent

Engineering teams were required to prove that every new subsystem design aligned with dense, government-issued defense guidelines—documents that often span hundreds of pages and are updated frequently. Historically, compliance engineers manually compared design specifications to guideline requirements, highlighting gaps, drafting review reports, and routing findings back to designers. This work was slow, error-prone, and varied widely depending on who performed the review. Missing a single requirement could delay certification, introduce rework, or trigger a failed audit.

Using StackAI, the contractor deployed an Engineering Design Compliance Agent that transforms this process. Engineers upload the design specification or subsystem description, and an open source LLM automatically summarizes the design into a clear abstract. StackAI then orchestrates additional steps in which the agent searches internal engineering rulebooks and the full set of defense guidelines, identifying which requirements apply. The system generates a structured report outlining relevant standards, non-compliant sections, ambiguous areas, and recommended fixes. For complex designs, the workflow breaks into multiple LLM reviewers—each step logged, reviewable, and auditable, giving engineering management unprecedented clarity and consistency in compliance reviews.

RFP Response Agent

Responding to structured government RFPs was one of the contractor’s most time-consuming business development tasks. Each RFP arrived with dozens of detailed questions, compliance matrices, and form-based requirements that demanded precise, approved language. Teams needed to pull from product documentation, cybersecurity certifications, program histories, and past performance narratives, all while ensuring consistency across responses and avoiding claims that legal had not vetted. The process often required long nights of manual work, with significant risk of overlooking mandatory sections or misinterpreting requirements.

With StackAI, the contractor built an RFP Response Agent that handles this complexity end-to-end while remaining fully on-prem. The agent ingests the full RFP and extracts each requirement. It then searches across internal knowledge bases for accurate, approved language covering capabilities, security posture, and program experience. Using an open-source LLM, the agent drafts each response section, fills in compliance tables, and assembles the full document into the company’s standard format. Capture managers review a coherent draft anchored in traceable internal materials instead of patchwork language pulled together under deadline pressure. The result is faster, more consistent, and more compliant proposals.

Compliance Package Generator

Preparing RMF (Risk Management Framework) or ATO (Authority to Operate) packages was historically one of the contractor’s most labor-intensive workflows. Analysts were required to gather evidence from numerous systems, map each evidence artifact to specific NIST controls, identify contradictions across logs and policies, draft narrative justifications, and assemble comprehensive reports. A single compliance package could take weeks and required meticulous manual effort from senior cybersecurity and governance specialists. Small errors or mismatches often triggered time-consuming rewrites or delays in authorization.

StackAI enabled the contractor to build a multi-agent Compliance Package Generator that automated this workflow while preserving auditability and security. Evidence documents, logs, and test results are uploaded and normalized through one agent, which extracts relevant details. A second agent maps each evidence item to the appropriate NIST control or internal governance requirement, automatically flagging gaps or contradictory data. A third agent validates the mappings to ensure consistency across all controls. Finally, a report-drafting agent fills the official RMF/ATO template, generating polished narrative sections, control summaries, and references, in a fraction of the time.

Compliance Package Generator

Proposal Reference Agent

Proposal teams at the contractor were constantly under pressure to turn around large, competitive bids in extremely tight windows. But the information they needed (past proposals, customer language, pricing notes, approved legal boilerplate, technical writeups) was scattered across years of SharePoint folders and internal drives. Reusing high-quality material was nearly impossible, and capture managers routinely spent days hunting for content or rewriting sections that already existed. The result was slow proposal cycles, inconsistent quality, and an over-reliance on a handful of senior staff who knew where previous materials lived.

With StackAI, the contractor built an on-premise Proposal Reference Agent that allowed teams to upload a new RFP or provide a short description of the opportunity, then instantly surface relevant excerpts from previous bids, best-fit technical language, program summaries, and legal-approved phrasing. The agent runs entirely on a self-hosted open-source LLM and produces a curated brief with reusable paragraphs, contextual recommendations, and citations pointing back to the original documents in SharePoint. Instead of starting from scratch, proposal teams now begin with a structured, compliant first draft assembled in minutes, dramatically accelerating the capture process while improving consistency across submissions.

Conclusion

StackAI empowered this contractor to introduce AI into sensitive engineering, proposal, and compliance workflows without compromising security requirements or changing their existing operational posture. By running agents entirely on-premise, using their own open-source LLMs, they were able to automate high-volume, document-heavy tasks while keeping all data, inference, and logging inside their controlled environment.

What made StackAI the best fit for this setting was its alignment with defense-sector constraints: the ability to deploy locally, integrate with internal repositories, enforce governance, and orchestrate multi-step agents without relying on external services. Instead of introducing new risks or parallel shadow systems, the platform helped standardize how teams handle large volumes of technical documentation. It provided a controlled way to use AI where it was already needed, within the boundaries of a secure, regulated environment where accuracy and accountability matter as much as speed. Want to see how StackAI can do the same for your enterprise? Get a demo here.

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