Sana Fathima's Work | ContraWork by Sana Fathima
Sana Fathima

Sana Fathima

AI Engineer automating workflows & web apps

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Cover image for Built an AI-powered marketing automation
Built an AI-powered marketing automation workflow that turns a simple prompt into fully generated and published social media campaigns. The workflow: Refines prompts using AI Generates creatives through Canva Adds a human approval layer Publishes content to LinkedIn, Facebook, and X automatically Captures leads and updates dashboards in real time If content gets rejected, the workflow automatically regenerates improved versions and retries the process. Built using n8n, AI integrations, Canva API, and automated lead capture systems. If you're looking for customized automation workflows tailored to your business or use case, feel free to reach out. #AI #Automation #WorkflowAutomation #n8n #AIAutomation #MarketingAutomation #LeadGeneration #CanvaAPI #BusinessAutomation #AIWorkflows
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Automated Cybersecurity Monitoring & Alert System – Workflow-Driven Security (n8n)   • Deployed n8n workflows to monitor 15+ log sources, detecting unauthorized access across 50+ servers.   • Sent 500+ detailed alerts weekly, improving incident response time by 45%.   • Scaled centralized logging & alerting, handling 1.2M+ log entries per month without failures.
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Cover image for Creative work
Creative work
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Automated Cybersecurity Monitoring & Alert System – Workflow-Driven Security (n8n)   • Deployed n8n workflows to monitor 15+ log sources, detecting unauthorized access across 50+ servers.   • Sent 500+ detailed alerts weekly, improving incident response time by 45%.   • Scaled centralized logging & alerting, handling 1.2M+ log entries per month without failures.
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Smart Agriculture Assistant – Multilingual Voice Platform (MERN, Gemini, Groq)   • Built AI-based image recognition to identify plant diseases and suggest remedies for 5K+ simulated users.   • Integrated multilingual voice assistant + real-time weather and market APIs, providing 24/7 farmer support.   • Improved backend scalability by sharding MongoDB and load-balancing APIs, boosting throughput by 40%.
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