Security Design ReviewCross-industryPublished February 5, 2026

Scale Security Design Reviews (SDR) for Modern AppSec Teams

Executive summary

What this whitepaper covers

Security teams are expected to review every feature, but there simply aren't enough of them to do it. The tools that exist: SAST, DAST, SCA only come into play once code already exists. By then, the architectural decisions that really matter have already been made. Security design reviews (SDRs) solve this problem by identifying vulnerabilities before code is written but in practice, they are difficult to scale due to limited expertise and unstructured inputs.

This whitepaper explores how AI-powered SDRs analyze design documents, architecture diagrams, and engineering artifacts and generate security requirements early before vulnerabilities are introduced into code.

It also introduces key capabilities such as compliance mapping, asset inventory generation, and integration with existing tools like Jira and Slack. Importantly, this is not about replacing human expertise. Instead, automation handles baseline analysis, allowing security engineers to focus on high-impact decisions.

It highlights how Seezo SDR enables 100% coverage by ensuring every feature undergoes a review, without requiring additional AppSec headcount.

For AppSec teams struggling with scale, this paper provides a clear path to embedding security design reviews into every development workflow without slowing down delivery.

Key findings

What you'll take away

  • ✦Traditional AppSec tools miss design-stage vulnerabilities
  • ✦SDRs help prevent issues before code is written but manual SDRs can't scale at a 2:100 AppSec-to-developer ratio
  • ✦AI enables scalable, automated SDRs across all features
  • ✦Security requirements can be generated early in the SDLC
  • ✦Integration into developer workflows is critical for adoption
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FAQ

Frequently asked questions

What inputs does Seezo SDR accept?
Existing design documents wherever they live: Jira, PDFs, Confluence, Google Docs, and Slack. Architecture diagrams are also supported and produce deeper analysis when provided.
How does Seezo keep LLM output reliable?
Two techniques combined. Retrieval-augmented generation (RAG) grounds the model in the actual design documents. Decision-tree prompt engineering forces yes/no answers instead of open-ended ones, which reduces hallucination.
How long does a typical review take?
Seezo generates a security summary, open questions, security requirements, and compliance mapping in about 10 minutes. A spot check by a human reviewer runs around 60 minutes on top of that for high-risk features.
Which integrations are live today?
Seven at launch: Google Drive, Notion, SharePoint, Confluence, Jira, Slack, and ServiceNow. The roadmap adds 10 plus more over the next six months including GitHub, Miro, and Lucidchart.