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VamiAppSec is an AI-assisted application security platform developed during my professional experience at VamiSec GmbH.
I contributed to integrating automated security analysis into development workflows, combining multiple security scanning technologies with AI-assisted vulnerability analysis.
My contributions included:
• Integrating SAST, SCA, and secrets detection tools.
• Automating security scanning through CI/CD pipelines.
• Implementing Infrastructure-as-Code security checks.
• Supporting SBOM generation and dependency analysis.
• Developing security findings aggregation and reporting workflows.
• Integrating AI-assisted vulnerability triage and remediation guidance.
Technologies: Python, GitHub Actions, Semgrep, Gitleaks, Checkov, Syft, Grype, LLMs, DevSecOps.
This experience strengthened my expertise in application security engineering, security automation, and AI-assisted DevSecOps.
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Awesome dude
Before you add AI to your product, find the screen where your users already copy and paste.
That's usually where the real AI feature lives. Not a chatbot in the corner, but a step people already do by hand: summarising a ticket, drafting a reply, tagging an upload, pulling fields out of a PDF.
Here's the order I follow when a founder asks me to add AI to an existing SaaS:
1. Pick one workflow, not "AI everywhere." Watch where users leave your app to paste something into ChatGPT and come back. That round trip is your feature.
2. Keep the model behind your own API. One service owns prompts, retries, logging and cost limits, so you can switch providers without touching the frontend.
3. Make it tenant-aware from day one. Each customer's data, prompts and usage stay scoped to their account, or the first enterprise security review will stop you.
4. Ship a draft, not a decision. Let the AI suggest and the user approve. You earn trust and get real feedback before you automate anything.
5. Measure accepted output, not tokens. If users rewrite most of what it produces, the prompt or the context is wrong, and that's your real roadmap.
Most AI features that flop didn't fail because of the model. They were bolted onto the wrong step.
What's the one task your users still copy into ChatGPT?
Watching where users paste into ChatGPT and come back is such a practical way to find the real feature. Most teams start with the chatbot instead.
Percept AI – AI-Powered Customer Intelligence Platform
Designed a modern SaaS website for Percept AI, an AI-powered customer intelligence platform that helps businesses understand customer interactions, analyze behavioral signals, and turn insights into actionable strategies. The design features a clean layout, intuitive data dashboards, AI workflow visualizations, feature highlights, customer success stories, and a responsive interface with a premium visual style.
