1:"$Sreact.fragment"
2:I[91389,["/_next/static/chunks/d9e0d68f528a2dc6.js","/_next/static/chunks/ea6bdb0d940bcd8e.js","/_next/static/chunks/537d354b60c3ef65.js"],"default"]
3:I[97367,["/_next/static/chunks/ff1a16fafef87110.js","/_next/static/chunks/d2be314c3ece3fbe.js"],"OutletBoundary"]
4:"$Sreact.suspense"
0:{"buildId":"bJ-pHYGFcnjokhVAm8kTC","rsc":["$","$1","c",{"children":[["$","main",null,{"className":"min-h-screen bg-[#F8F9FA]","children":["$","$L2",null,{"project":{"id":"3","title":"Social Trend Predictor","description":"An ML-powered social media management platform that simplifies content creation, scheduling, and uses predictive analytics to identify viral trends before they peak.","image":"https://images.unsplash.com/photo-1611162617474-5b21e879e113?q=80&w=1974&auto=format&fit=crop","link":"/portfolio/3","category":"Marketing Tech","year":"2024","duration":"5 Months","technologies":["Vue.js","Django","PyTorch","Redis","Celery","GCP"],"features":["Real-time ingestion and NLP analysis of millions of social media posts per day.","Keyword sentiment tracking and velocity scoring across Twitter, Reddit, and LinkedIn.","Industry-specific trend alert system with configurable notification thresholds.","Competitor brand monitoring and share-of-voice tracking.","Content calendar integration suggesting optimal posting times for each platform.","Interactive analytics dashboard with trend visualizations and historical comparisons."],"challenge":"A global PR firm needed a competitive edge to help their clients stay ahead of the hyper-fast news cycle. Relying on gut feeling and delayed analytics reports meant they were constantly reacting to trends instead of capitalizing on them as they emerged.","solution":"We built the Social Trend Predictor, a real-time data ingestion engine capable of processing millions of global social media posts daily. Using natural language processing (NLP) models built with PyTorch, the system gauges sentiment and velocity of keywords. The intuitive dashboard alerts PR managers to emerging topics specific to their clients' industries days before they hit mainstream media.","results":["Processed over 50 million social data points daily with sub-second latency.","Identified 14 major industry trends an average of 3 days prior to peak virality.","Boosted client engagement metrics by 41% through hyper-relevant, perfectly timed posting.","Reduced manual trend-research time by 85%."]}}]}],[["$","script","script-0",{"src":"/_next/static/chunks/537d354b60c3ef65.js","async":true}]],["$","$L3",null,{"children":["$","$4",null,{"name":"Next.MetadataOutlet","children":"$@5"}]}]]}],"loading":null,"isPartial":false}
5:null