From approved intent to enforced release decisions.
SecureShift AI connects what your team approved at design review to what is allowed at merge. It converts intent into enforceable requirements and keeps those decisions consistent through delivery.
Intent in. Enforced outcomes out.
No parallel process required. SecureShift AI works with your existing tooling and returns decisions where teams already collaborate.
Catch it on paper
Design docs and threat models are reviewed and distilled into clear, versioned security requirements.
Verify every change
Each pull request is checked for code that drifts from approved intent, and whether a finding is actually exploitable.
Decide the merge
Four stages, one continuous control loop.
Ingest intent
SecureShift AI connects to GitHub, Jira and Confluence and reads the security decisions already embedded in your design docs, threat models and tickets.
- Design docs & PRDs parsed for security-relevant decisions
- Threat models mapped to concrete controls
- Existing standards and patterns ingested as priors
Generate requirements
Each decision becomes a precise, testable security requirement, versioned, traceable, and bound to the code path it governs.
- Plain-language intent → machine-checkable rule
- Every requirement carries an owner and a source
- Versioned so changes are auditable over time
Enforce at the gate
Requirements become required status checks on the pull request. Code that contradicts approved intent is refused, not just annotated.
- Native required checks, no parallel dashboard
- Clear, attributable reason on every block
- The engineer sees exactly what to change
Prove it
Every verdict is logged with its source decision, producing a defensible trail from design choice to enforced control, ready for audit.
- Decision → requirement → verdict, end to end
- Exportable evidence for SOC 2, PCI and friends
- Trend coverage across teams and repos
From design intent to merge-gate authority.
SecureShift AI unifies design review, verification, and merge enforcement so approved intent remains actionable at every release checkpoint.
Security Design Intent
SecureShift AI acts as the definitive System of Record for all security requirements and design-time decisions.
- Automated intent capture — ingests PRDs, Jira epics, and architecture diagrams to identify threats before a single line of code is written.
- Structured requirements — findings become trackable requirements mapped to internal policies and regulatory frameworks.
- Centralized governance — a permanent, auditable record of the "why" behind every security decision across the SDLC.
Policy Enforcement
We turn static records into a System of Action by sitting directly in the developer's merge path.
- The SDLC Interceptor — owns the pre-CI step, enforcing design intent at the merge gate.
- Automated design validation — every PR evaluated against cumulative approved design context; contradictions are flagged or blocked by policy.
- Zero-friction guardrails — clear, traceable reasoning back to the original design review so developers self-correct without ProdSec intervention.
Built for evolving product-security mandates.
Additional capabilities extend the same control model to emerging risk categories such as autonomous systems and quantum-era cryptography.
Agent security from design to monitor
A purpose-built lifecycle guiding any autonomous AI agent through SecureShift AI's design → code → gate → monitor pipeline — grounded in OWASP Agentic Top 10 2026 (ASI01–ASI10).
SecureShift AI threat-models agents before deployment, generates runtime enforcement policies, and continuously verifies post-deployment behavior against approved controls.
Explore Agentic AI Onboarding →Post-quantum readiness at the SDLC layer
An agentic subsystem embedded natively in the design → code → gates pipeline — built for Harvest Now, Decrypt Later (HNDL) attacks, where adversaries capture encrypted data today to decrypt once quantum computers mature. Generates Cryptography Bill of Materials (CBOM), scores HNDL risk, and executes autonomous remediation.
SecureShift AI identifies quantum-vulnerable cryptography early, prioritizes it by data context, and generates migration-ready implementation guidance before release.
Explore QCRE →Runs inside your current operating stack.
Your engineers, security team, and PMs keep working in familiar tools while SecureShift AI provides consistent, attributable control decisions.
…plus anything else you run, through our REST API & webhooks.
Design becomes policy.
Policy becomes the gate.
See how your approved security intent becomes an enforceable release control on your own stack.