Product Design for SaaS, AI & Fintech Companies
A modern landing page animation designed for a self-discovery and personal growth platform. This scrolling website concept transforms the browsing experience through smooth motion, immersive transitions, and a clean visual hierarchy that guides users from an emotional hero section into an interactive overview of the product. The animation is crafted to make storytelling feel natural while reinforcing the brand's premium identity.
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AI Security & DevSecOps Engineer | Cloud Automation
SafeShell | Secure Command Execution & Linux Sandboxing (https://github.com/HamzaGhebriche/SafeShell)
SafeShell is an open-source Python security tool I developed to inspect potentially dangerous shell commands, enforce execution policies, and run permitted commands within a restricted Linux sandbox.
The project focuses on improving command execution safety in development environments, automation workflows, and security-sensitive applications.
🔐 Key Features
1. Command Security Analysis
Inspects shell commands before execution.
Identifies potentially dangerous command patterns.
Generates structured findings and risk information.
Supports deterministic command analysis without executing the submitted command.
2. Secure Linux Sandboxing
Uses Bubblewrap and Linux security controls to restrict command execution.
Implements Linux namespaces and seccomp-based restrictions.
Reduces access to host resources through controlled filesystem and runtime configurations.
Refuses protected execution when required security mechanisms are unavailable.
3. Security Policies & Access Control
Enforces configurable offline execution policies.
Supports explicit authorization for permitted operations.
Prevents approvals from overriding hard security restrictions.
Provides structured execution decisions and status information.
4. Security Automation & Auditing
Offers a Python command-line interface.
Supports JSON output for integration with automation workflows.
Records local execution metadata for review.
Provides timeout and output-size controls.
5. Cross-Platform Development
Supports command inspection and policy management on Linux, Windows, and macOS.
Provides protected execution on supported Linux environments.
Includes automated validation through CI pipelines.
Technologies: Python, Linux, Bubblewrap, seccomp, Linux Namespaces, Bash, GitHub Actions, JSON, Security Automation.
My Role: Independent Developer & Security Engineer.
Project Type: Open-source security tool.
Current Status: Experimental alpha release (v0.1.0-alpha).
SafeShell has undergone automated testing but has not received an independent security audit. It is not intended to serve as a production-grade security boundary.
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MCP Security Auditor | AI Agent & MCP Server Security (https://github.com/HamzaGhebriche/mcp-security-auditor)
MCP Security Auditor is an open-source security analysis tool I developed to help engineers identify security risks in Model Context Protocol (MCP) servers and AI-agent integrations.
As AI agents increasingly connect to external tools, APIs, and sensitive data, securing these integrations becomes essential.
I designed and developed MCP Security Auditor to automate security configuration reviews, identify potentially dangerous implementation patterns, and generate actionable security reports.
Key Features:
🔐 MCP Security Analysis
Detects risky authentication and authorization configurations.
Identifies potentially unsafe tool permissions and execution patterns.
Reviews filesystem access and security boundaries.
🤖 AI Agent Security
Analyzes security configurations used in MCP integrations.
Identifies potentially insecure connections between AI agents and external tools.
Supports security reviews of AI-powered applications.
⚙️ Automated Security Auditing
Static analysis of Python code and configuration files.
Automated security findings with severity classifications.
Security reports in JSON, HTML, Markdown, and SARIF formats.
Configurable security policies and risk scoring.
🚀 DevSecOps Integration
Supports automated security checks in development workflows.
Helps developers identify security issues earlier.
Provides actionable findings to support remediation.
Technologies: Python, MCP, Static Application Security Testing, Security Automation, GitHub Actions, JSON, YAML.
Business Value: Helps development teams review MCP integrations, identify risky configurations, and introduce repeatable security checks into their development processes.
My Role: Independent Developer & Security Engineer.
Project Type: Open-source cybersecurity tool.
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VamiAppSec | AI-Powered Application Security Platform (https://vamiappsec.com/#top)
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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AI Agent Security Testing & Assessment | AgentGuard (https://github.com/HamzaGhebriche/AgentGuard)
AgentGuard is an open-source AI agent security testing tool designed to help developers assess the security of AI-powered applications and agentic systems.
I developed AgentGuard to support structured security assessments of authorized AI-agent endpoints, identify security weaknesses, and verify whether implemented fixes address the observed issues.
Key capabilities include:
• AI-agent endpoint security assessments.
• Testing of authorization and access-control behavior.
• Security findings with supporting evidence.
• Comparison of vulnerable and corrected application behavior.
• Local dashboard for reviewing and exporting security reports.
• Automated security testing using Python.
The project helps development teams understand security risks in their AI applications and validate specific security improvements.
Technologies: Python, AI Agent Security, LLM Security, API Security, Security Automation.
Project: AgentGuard — Open Source Security Tool.
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n8n Expert | AI Automation & CRM Workflows
n8n Expert | AI Automation & CRM Workflows
Multi-Modal Telegram AI Agent (n8n Workflow Automation)
I built a production-ready, multi-modal Telegram AI Agent utilizing n8n to automate complex conversation routing and media processing. The system dynamically intercepts text, voice notes, and images, routing them through specialized pipelines for real-time contextual analysis.
Key Features & Architecture:
Smart Conditional Routing: Implemented intelligent switch routers that automatically separate user intent based on incoming media types (Chat, Voice, or Image).
Voice-to-Text Pipeline: Integrated automated voice note retrieval coupled with OpenAI Whisper transcription models to convert spoken audio into structural prompt data.
Advanced Vision Analytics: Developed an image processing route that extracts, analyzes, and interprets visual uploads using OpenAI Vision capabilities.
Custom Engine Extensions: Embedded custom JavaScript code nodes to run custom data transformations, variable styling, and cleaner payload processing.
Dynamic Audio Generation: Configured text-to-speech feedback loops allowing the agent to respond automatically back to Telegram with freshly synthesized voice messages or contextual alerts.
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🚀 Still Processing Invoices Manually? Here's How AI Automation Can Transform Accounts Payable.
🔴 The Business Problem
Finance teams often struggle with:
❌ Duplicate invoices and potential double payments
❌ Manual PDF data entry and verification errors
❌ Time-consuming vendor, bank, PO & GRN checks
❌ Delayed approvals and disconnected ERP systems
❌ Poor exception visibility and limited audit tracking
🟢 My Solution: Enterprise AI Invoice Automation using n8n
I designed an intelligent invoice processing workflow combining AI, database validation, business rules, and human oversight.
⚙️ Key Capabilities
✅ Duplicate Detection: MD5 document hashing + PostgreSQL-based duplicate verification.
✅ AI Document Intelligence: Automated invoice extraction and structured data processing.
✅ Vendor & Fraud Validation: PostgreSQL lookups, banking verification, and fraud-checking logic.
✅ ERP & Procurement: Purchase Order, Goods Receipt (GRN), and BOM data integration.
✅ Currency Automation: Live exchange-rate APIs and JavaScript calculations.
✅ Human-in-the-Loop: Manual approval for invoices requiring additional verification.
✅ Error Handling: Exception routing, failure alerts, and controlled recovery workflows.
✅ Automated Notifications: Gmail and Telegram alerts for processing updates.
💼 Business Value
✔ Reduce repetitive manual verification
✔ Strengthen duplicate-payment prevention
✔ Improve invoice processing consistency
✔ Maintain human control over critical approvals
✔ Connect finance, procurement, and database systems
🛠 Tech Stack: n8n | AI | PostgreSQL | JavaScript | REST APIs | Gmail | Telegram
🎥 Watch the workflow demonstration.
I'm available for custom AI automation, n8n development, Accounts Payable solutions, and enterprise system integrations.
If your finance team is spending hours validating invoices manually, let's discuss how automation could simplify the process.
#n8n #AIAutomation #AccountsPayable #InvoiceAutomation #FinanceAutomation #PostgreSQL
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🚀 Is Your Customer Support Team Spending Too Much Time on Repetitive Tasks?
Customer enquiries, delayed responses, manual ticket handling, and disconnected systems can slow down business operations.
I build AI Business Assistant solutions using n8n, AI Agents, and API integrations.
Here's what the solution can automate:
✅ Customer enquiry classification and response drafting
✅ Priority-based routing and escalation
✅ Ticket creation and tracking
✅ CRM updates and team notifications
✅ Human-in-the-loop approvals for complex cases
✅ Integration with existing business tools
The goal: Faster response handling, less repetitive work, and better operational visibility.
I've built working AI assistant and customer support automation demonstrations and am available for custom implementation and subcontracting projects.
Are you a business owner, operations manager, or automation agency looking to automate customer support?
📩 DM me with your requirements. I'll share a relevant workflow demo and discuss a fixed-price implementation.
#n8n #AIAgents #CustomerSupportAutomation #BusinessAutomation #AIIntegration
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🚀 Built: Enterprise ISO Guard Final - AI Agent OS
Tired of manual compliance checks? I automated it.
Workflow:
Input (Telegram/Voice) → Switch Logic → HTTP Requests + Audio Transcription →
AI Agent (Google Gemini + Postgres Chat Memory) →
PDF Creation + Airtable + Gmail + Telegram Alert
Tech: n8n, Gemini, Postgres, Telegram API, Custom JS
Result: 15 hours/week of manual review → 100% automated, zero errors.
I have 15+ such production workflows live - Lead Qualification + CRM, GST Reconciliation, Supply Chain Cost Engine.
Building similar automation? DM me.
#AI Automation #n8n #AIAgent #WorkflowAutomation #Gemini
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Crafting User-Centric Designs with Framer & React
Managing Director | MIT | Harvard | Wharton | LSS MBB
Hello, I'm Rogério Almeida, Founder and CEO of VETRA STRD.
My professional background combines strategic management, intelligence methodologies, and technology.
At VETRA, we are developing artificial intelligence solutions designed to help organizations make better, more informed decisions.
Our work focuses on strategic intelligence, open-source intelligence, corporate due diligence, and enterprise risk analysis.
We believe that artificial intelligence should do more than generate answers. It should help transform information into reliable, actionable intelligence.
Our portfolio includes VETRA STRD, VETRA Legal, and VETRA Editorial, each designed to address specific professional and business needs.
Our mission is to combine advanced technology, disciplined methodology, and human expertise to deliver meaningful results.
I invite you to explore our projects and discover how VETRA can support your business.
I'm Rogério Almeida, and this is VETRA.
Intelligence Beyond Data.
https://www.youtube.com/watch?utm_source=chatgpt.com&v=Q4BYMLXMK-E&feature=youtu.be
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Workflow automation for forms, CRMs, Zapier, Make, n8n.
Self-initiated internal product. Odds Desk uses public data only. It is not client work, a trading tool, or financial advice.
I built this because a research brief is only as trustworthy as the source snapshot behind it. Catalog freshness, derived summaries, file identity, and editorial status need to stay consistent across every generated artifact.
The workflow synchronizes a public catalog, exports one canonical bundle, generates and validates a summary, regenerates a manifest, checks declared SHA-256 values against disk, and produces a dashboard and Markdown brief from the same saved files.
The workflow fails closed. If a required validation fails, the bundle stops, the evidence is preserved, and no buyer-ready issue is produced.
The gallery shows a July 30, 2026 snapshot with 675 saved markets, 36 unverified research leads, zero verified cards, and four of four declared hashes matching disk. The state remains RESEARCH_PREVIEW.
Best fit: public API ingestion, reproducible research bundles, validation pipelines, provenance checks, fail-closed editorial workflows, and automated briefing systems.
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A self-initiated workflow automation demo showing a simple lead handoff: intake, routing, CRM or sheet logging, owner notification, and test-ready review output.
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A self-initiated Brief Factory internal system. The gallery shows public post titles only. No names, handles, contact details, or private messages are shown.
I built this to make public automation research more consistent. Instead of manually checking communities for scattered requests, the monitor reads selected RSS and Atom feeds, normalizes source URLs, rejects stale or generic items, scores observable workflow pain, deduplicates accepted rows, and records source health.
The output is a structured review queue, not permission to contact anyone. The system does not post, bid, message, or send.
The gallery shows a dated run from July 30, 2026: seven configured feeds, seven review rows, two HTTP 429 rate limits, zero high-intent rows, and zero external actions authorized.
Best fit: public-source monitoring, qualification queues, source-health reporting, research triage, and review-first opportunity workflows.
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Full-Stack Engineer | AI Automation & Workflow Systems
Built an AI-powered news automation system using n8n and Google Sheets that collects articles, filters data, processes content with AI, and automatically updates structured records for marketing insights and content tracking.
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Outbound Lead Generation & Automation System (Email + LinkedIn)
I built a complete outbound system to generate and convert high-quality B2B leads using email and LinkedIn automation.
The system starts with ICP-based lead sourcing, targeting companies by size, revenue, industry, and C-level roles. Leads are enriched, segmented, and automatically routed into a structured outreach flow.
I designed a 6-step email sequence where messaging evolves at each step to increase reply rates. LinkedIn actions are timed between email touches to create a natural multi-channel outreach without overlap.
The main challenge was coordinating multiple tools while maintaining deliverability and clean data flow. I solved this by building a centralized automation layer that handles sequencing logic, delays, and real-time updates across systems.
A lightweight CRM tracks every lead from first contact to final outcome, including replied, interested, and not interested. This provides clear visibility and allows continuous optimization.
The system is structured for scalability and simple handoff, so it can be managed without technical dependency.
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Built a feedback and workflow management system focused on collecting, organizing, and prioritizing user-driven inputs across multiple channels. The platform provides a structured interface where feedback items move through defined stages, enabling teams to track status, engagement, and impact in a clear and scalable way.
On the backend, I designed data models and filtering logic to support advanced querying, segmentation, and lifecycle management of feedback items. Implemented role-based access control and admin-level configurations to manage permissions, visibility, and workflow transitions. This ensures that internal teams can efficiently manage large volumes of data while maintaining consistency and control.
On the frontend, I focused on building clean dashboards and interactive views that surface key metrics such as user reach, engagement, and revenue impact. I also implemented public-facing and read-only views, allowing external users to submit feedback and track updates without direct system access. This improves transparency while keeping the system secure and well-structured.
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I built a workflow management system focused on tracking projects from start to completion with clear visibility and control at every stage. The core of the system is a multi-role dashboard that presents real-time data in a structured way, allowing different users to quickly understand project status, performance metrics, and operational health without digging through raw data.
On the backend side, I designed structured data models and lifecycle flows to manage how tasks move through different stages (creation → in-progress → completed). I implemented role-based access control and admin-managed configurations so the system can handle multiple users, permissions, and dynamic updates reliably. The goal was to make the system scalable and maintainable while keeping the logic clean and predictable.
For the frontend, I focused on building intuitive dashboards and reporting layers that translate complex data into simple, actionable insights. I also implemented shareable, read-only views so external users can track progress through a secure link without needing full access. This improves transparency while maintaining control over the system, which is critical for B2B workflow tools.
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Web Development/Content Creator/Animator
