AI-augmented security built into how you ship code.

We do it gradually and we tune as we go. We start with the rules that give you the most signal and the least noise for your stack, work to keep false positives down, and run everything in warning mode for a while before it starts blocking. In steady state, most teams see under five minutes added to pipeline time and fewer than two extra PR comments a week.

We triage that list first to separate genuine risks from noise. Then we agree on a remediation backlog ordered by exploitability, and we set the CI gate so it only blocks new findings. The legacy debt gets cleared on a schedule you've signed off on, so it never turns into a fire drill.

Yes. That's actually most of our DevSecOps work. We review what's already there, point out the gaps, and add tooling piece by piece. There's no need to rewrite the pipeline.

Fast checks run on every commit and pull request: secret scanning, dependency audits, and SAST, so developers get feedback in minutes. Slower checks like DAST and full container scans run on the staging deploy. A pre-deploy gate to production is the last line, blocking a release when high or critical findings are still open.

We tune the rule set to your stack, suppress known-safe patterns, and use LLM-assisted triage to filter noise before anything reaches a developer. New rules start in warning mode so the team sees the signal quality before it ever blocks a merge. The goal is fewer than two extra PR comments a week, and we keep adjusting until we hit it.

They only slow you down if they are noisy or badly placed, which is exactly what we tune out. Findings appear as inline PR comments with a suggested fix, in the tools developers already use, rather than as a separate ticket queue. Most teams see under five minutes added to pipeline time once tuning settles.

For SAST we typically use Semgrep or CodeQL, for dependencies Snyk or the native scanners (npm audit, OWASP Dependency-Check), and for DAST tools like OWASP ZAP against staging. Container scanning uses Trivy or Snyk Container. We pick based on your languages and existing toolchain rather than forcing one stack on you.

We deploy a secrets manager such as HashiCorp Vault or AWS Secrets Manager, rotate any existing secrets, and scan the full git history for leaks. Pre-commit hooks and CI secret scanning then block new secrets before they are committed. Developers pull secrets at runtime instead of hardcoding them, so a leaked repository no longer means leaked credentials.

Yes. The threat models, scan reports, secrets management records, and deployment-gate logs become the evidence package auditors ask for. Automated controls in CI also give you continuous proof that checks run on every change rather than a once-a-year snapshot. We structure the outputs so they map cleanly to ISO 27001 and SOC 2 control requirements.

We add controls mapped to the OWASP LLM Top 10, covering prompt injection, insecure output handling, and sensitive data leakage through RAG. Tests for those failure modes run alongside your existing SAST and DAST so AI surfaces are checked on the same cadence as the rest of your code. The threat model from the design stage already accounts for these risks, so the pipeline checks reinforce decisions made early.