From approved intent to enforced release decisions.
SecureShift AI connects approved design intent to merge decisions. It turns intent into release rules and keeps them consistent from design review through delivery.
Approved intent in. Clear release decisions out.
No parallel workflow to manage. SecureShift AI works in your existing toolchain and returns decisions where teams already work.
Define it in design
Design docs and threat models are reviewed and converted into clear, versioned security requirements.
Check every pull request
Each pull request is checked for drift from approved intent and whether findings are truly exploitable.
Decide the merge
Four stages, one business-accountable 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
Capture intent. Enforce it at merge.
One place for approved rules; one gate that enforces them. SecureShift AI carries approved decisions from design review to the merge gate.
Capture the rule
Approved requirements and design decisions stay in one place.
- Automated intake: reviews PRDs, Jira epics, and architecture diagrams before code is written.
- Structured requirements: turns findings into trackable requirements tied to policy.
- Audit trail: keeps the reason behind each security decision visible.
Enforce the rule
Those approved decisions are checked directly in the merge path.
- Merge gate control: approved design intent is enforced before CI moves forward.
- PR validation: pull requests are checked against approved requirements; contradictions are flagged or blocked by policy.
- Clear guidance: developers see what failed and why without waiting on another review loop.
The same control model, applied to new risk areas.
Quantum readiness uses the same design-to-release enforcement loop.
Post-quantum readiness at the SDLC layer
A quantum-readiness capability in the same design-to-release workflow, helping teams prioritize risk and plan migration with business context.
SecureShift AI identifies quantum-vulnerable cryptography early, prioritizes it by data context, and produces migration-ready guidance before release.
Explore quantum readiness →Runs inside your current operating stack.
Your engineers, security team, and PMs keep working in familiar tools while SecureShift AI provides consistent, auditable release decisions.
…plus anything else you run, through our REST API & webhooks.
Walk through the platform on your stack.
See how design review, requirements, and merge enforcement connect in one traceable workflow.