Product teams selling software to enterprise customers
Govern
Application Security, AI & DevSecOps
Embed practical security into software and AI-enabled product delivery so teams can move faster with fewer late-stage surprises.
01Find vulnerabilities earlier in delivery
02Reduce recurring classes of defects
03Reduce AI integration, data handling, and model interaction risk
04Create evidence for customers and auditors
What is included
A complete, decision-ready engagement.
Final scope is tailored to your environment, objectives, and constraints. A typical engagement can include:
- Secure SDLC assessment and roadmap
- Threat modeling for critical workflows
- AI and LLM feature threat modeling
- Prompt injection, data leakage, and unsafe output review
- Model, API, RAG, and third-party AI integration review
- AI-generated code governance and secure review controls
- OWASP-aligned review of LLM and generative AI risks
- SAST, DAST, and dependency scanning strategy
- Secret scanning and credential hygiene
- CI/CD pipeline hardening
- Infrastructure-as-code scanning
- Container and cloud configuration review
- Software bill of materials readiness
- Security gates and exception workflows
- Developer-focused remediation guidance
A strong fit for
Organizations with a clear reason to act.
Engineering organizations formalizing DevSecOps
Teams introducing AI assistants, LLM features, or AI-enabled workflows
Teams preparing for SOC 2 or customer application reviews
Engagement model
Structured for control and momentum.
Scope, communication, and handoff are designed to work with enterprise stakeholders without creating unnecessary process.
Trace
Map repositories, pipelines, environments, AI data flows, model integrations, release controls, tools, and developer workflows.
Integrate
Place the right checks at the right stage with usable feedback and governed exceptions.
Improve
Measure recurring findings, tune controls, and mature the program without slowing delivery.
Questions
What buyers usually ask.
The scoping call covers environment-specific questions, dependencies, timing, and deliverables.
Will DevSecOps slow our release process?
The goal is the opposite. Well-placed checks and clear exception paths reduce late rework and make security decisions more predictable.
Can you work with our existing development tools?
Yes. Recommendations are shaped around your repositories, CI/CD platform, cloud, ticketing, and engineering practices.
Can you assess AI features and LLM integrations?
Yes. We can review AI data flows, trust boundaries, prompt injection exposure, sensitive data handling, model and API integrations, output controls, and the development practices surrounding AI-enabled features.
Application, AI & DevSecOps
Turn this priority into a controlled plan.
Use the scoping call to confirm the objective, environment, stakeholders, and right-sized engagement before making a commitment.