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Elvir

@elvirt

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Full-Stack AI Developer (AI, Mobile, Shopify...)

$30 USD / Hour

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Flag of GERMANY

Germany (3:35 PM)

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Joined on July 8, 2026

$30 USD / Hour

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Senior full-stack dev (React Native/Flutter + Shopify + AI). I build cross-platform mobile apps, custom Shopify solutions, and embed intelligent features like recommendations, search, and chatbots. Strong communicator, accurate estimator, and team mentor. Let's build something great.

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Portfolio

Portfolio

14001775
Developed a custom Shopify app that notifies customers the moment their favorite products drop in price, come back in stock, or launch as new collections. The app integrates seamlessly with the Shopify storefront using the Storefront API and Webhooks for real-time inventory and price tracking. Users can "watch" products with a single tap, set custom alert preferences (price threshold, stock status, or new arrivals), and receive instant notifications via email, SMS, or push notifications (on mobile). The app also includes a personalized dashboard where customers can manage their watched items and view alert history. Technical stack: Built with Node.js and Express for the backend, Shopify Polaris for the admin panel, and Firebase Cloud Messaging for push notifications. The frontend uses React with Hydrogen for a blazing-fast storefront experience. I also implemented Redis for caching to handle high-traffic events like flash sales. What makes it special: Real-time price and

Drop Alert - Shopify Shopper

Developed a custom Shopify app that notifies customers the moment their favorite products drop in price, come back in stock, or launch as new collections. The app integrates seamlessly with the Shopify storefront using the Storefront API and Webhooks for real-time inventory and price tracking. Users can "watch" products with a single tap, set custom alert preferences (price threshold, stock status, or new arrivals), and receive instant notifications via email, SMS, or push notifications (on mobile). The app also includes a personalized dashboard where customers can manage their watched items and view alert history. Technical stack: Built with Node.js and Express for the backend, Shopify Polaris for the admin panel, and Firebase Cloud Messaging for push notifications. The frontend uses React with Hydrogen for a blazing-fast storefront experience. I also implemented Redis for caching to handle high-traffic events like flash sales. What makes it special: Real-time price and

Drop Alert - Shopify Shopper

Developed a custom Shopify app that notifies customers the moment their favorite products drop in price, come back in stock, or launch as new collections. The app integrates seamlessly with the Shopify storefront using the Storefront API and Webhooks for real-time inventory and price tracking. Users can "watch" products with a single tap, set custom alert preferences (price threshold, stock status, or new arrivals), and receive instant notifications via email, SMS, or push notifications (on mobile). The app also includes a personalized dashboard where customers can manage their watched items and view alert history. Technical stack: Built with Node.js and Express for the backend, Shopify Polaris for the admin panel, and Firebase Cloud Messaging for push notifications. The frontend uses React with Hydrogen for a blazing-fast storefront experience. I also implemented Redis for caching to handle high-traffic events like flash sales. What makes it special: Real-time price and

Drop Alert - Shopify Shopper

Developed a custom Shopify app that notifies customers the moment their favorite products drop in price, come back in stock, or launch as new collections. The app integrates seamlessly with the Shopify storefront using the Storefront API and Webhooks for real-time inventory and price tracking. Users can "watch" products with a single tap, set custom alert preferences (price threshold, stock status, or new arrivals), and receive instant notifications via email, SMS, or push notifications (on mobile). The app also includes a personalized dashboard where customers can manage their watched items and view alert history. Technical stack: Built with Node.js and Express for the backend, Shopify Polaris for the admin panel, and Firebase Cloud Messaging for push notifications. The frontend uses React with Hydrogen for a blazing-fast storefront experience. I also implemented Redis for caching to handle high-traffic events like flash sales. What makes it special: Real-time price and

Drop Alert - Shopify Shopper

Developed a custom Shopify app that notifies customers the moment their favorite products drop in price, come back in stock, or launch as new collections. The app integrates seamlessly with the Shopify storefront using the Storefront API and Webhooks for real-time inventory and price tracking. Users can "watch" products with a single tap, set custom alert preferences (price threshold, stock status, or new arrivals), and receive instant notifications via email, SMS, or push notifications (on mobile). The app also includes a personalized dashboard where customers can manage their watched items and view alert history. Technical stack: Built with Node.js and Express for the backend, Shopify Polaris for the admin panel, and Firebase Cloud Messaging for push notifications. The frontend uses React with Hydrogen for a blazing-fast storefront experience. I also implemented Redis for caching to handle high-traffic events like flash sales. What makes it special: Real-time price and

Drop Alert - Shopify Shopper

14001761
Developed a cross-platform mobile app (iOS & Android) that turns any smartphone into an intelligent AI voice receptionist. The app allows business owners to manage incoming calls, schedule appointments, and handle customer inquiries — all from their mobile device, even when away from the office. The app connects to a cloud-based AI backend that processes calls using speech-to-text, natural language understanding, and text-to-speech. Users can view real-time call transcripts, listen to voicemail summaries, respond via chat or voice, and manage their availability — all through an intuitive, native-feeling mobile interface. Technical stack: Built with Flutter for cross-platform performance, Firebase for real-time sync and push notifications, and integrated with Twilio's Voice API for call handling. The app also features a beautiful, minimal dashboard with call analytics, sentiment insights, and calendar sync. What makes it special: Native-quality UI with smooth animations and gest

Smart Gadget Predictor Apps

Developed a cross-platform mobile app (iOS & Android) that turns any smartphone into an intelligent AI voice receptionist. The app allows business owners to manage incoming calls, schedule appointments, and handle customer inquiries — all from their mobile device, even when away from the office. The app connects to a cloud-based AI backend that processes calls using speech-to-text, natural language understanding, and text-to-speech. Users can view real-time call transcripts, listen to voicemail summaries, respond via chat or voice, and manage their availability — all through an intuitive, native-feeling mobile interface. Technical stack: Built with Flutter for cross-platform performance, Firebase for real-time sync and push notifications, and integrated with Twilio's Voice API for call handling. The app also features a beautiful, minimal dashboard with call analytics, sentiment insights, and calendar sync. What makes it special: Native-quality UI with smooth animations and gest

Smart Gadget Predictor Apps

Developed a cross-platform mobile app (iOS & Android) that turns any smartphone into an intelligent AI voice receptionist. The app allows business owners to manage incoming calls, schedule appointments, and handle customer inquiries — all from their mobile device, even when away from the office. The app connects to a cloud-based AI backend that processes calls using speech-to-text, natural language understanding, and text-to-speech. Users can view real-time call transcripts, listen to voicemail summaries, respond via chat or voice, and manage their availability — all through an intuitive, native-feeling mobile interface. Technical stack: Built with Flutter for cross-platform performance, Firebase for real-time sync and push notifications, and integrated with Twilio's Voice API for call handling. The app also features a beautiful, minimal dashboard with call analytics, sentiment insights, and calendar sync. What makes it special: Native-quality UI with smooth animations and gest

Smart Gadget Predictor Apps

Developed a cross-platform mobile app (iOS & Android) that turns any smartphone into an intelligent AI voice receptionist. The app allows business owners to manage incoming calls, schedule appointments, and handle customer inquiries — all from their mobile device, even when away from the office. The app connects to a cloud-based AI backend that processes calls using speech-to-text, natural language understanding, and text-to-speech. Users can view real-time call transcripts, listen to voicemail summaries, respond via chat or voice, and manage their availability — all through an intuitive, native-feeling mobile interface. Technical stack: Built with Flutter for cross-platform performance, Firebase for real-time sync and push notifications, and integrated with Twilio's Voice API for call handling. The app also features a beautiful, minimal dashboard with call analytics, sentiment insights, and calendar sync. What makes it special: Native-quality UI with smooth animations and gest

Smart Gadget Predictor Apps

Developed a cross-platform mobile app (iOS & Android) that turns any smartphone into an intelligent AI voice receptionist. The app allows business owners to manage incoming calls, schedule appointments, and handle customer inquiries — all from their mobile device, even when away from the office. The app connects to a cloud-based AI backend that processes calls using speech-to-text, natural language understanding, and text-to-speech. Users can view real-time call transcripts, listen to voicemail summaries, respond via chat or voice, and manage their availability — all through an intuitive, native-feeling mobile interface. Technical stack: Built with Flutter for cross-platform performance, Firebase for real-time sync and push notifications, and integrated with Twilio's Voice API for call handling. The app also features a beautiful, minimal dashboard with call analytics, sentiment insights, and calendar sync. What makes it special: Native-quality UI with smooth animations and gest

Smart Gadget Predictor Apps

14001751
Developed an intelligent AI voice receptionist system that automates incoming call management for businesses. The solution uses speech-to-text (STT) , natural language understanding (NLU) , and text-to-speech (TTS) to handle customer inquiries, schedule appointments, route calls to the right departments, and even take messages — all with human-like conversational flow. The system is built on Python with FastAPI for the backend, integrated with Twilio for telephony, and uses OpenAI's Whisper for STT and ElevenLabs or Google TTS for lifelike voice responses. The NLU layer is powered by a fine-tuned BERT-based model for intent classification and entity extraction. I also built a dashboard (Streamlit/React) for business owners to view call logs, transcripts, and analytics. What makes it special: Human-like conversational AI with < 300ms response latency. Multi-language support (English, Spanish, French) with real-time switching. Intelligent call routing — identifies caller intent a

AI Voice Receptionist & Call Manager

Developed an intelligent AI voice receptionist system that automates incoming call management for businesses. The solution uses speech-to-text (STT) , natural language understanding (NLU) , and text-to-speech (TTS) to handle customer inquiries, schedule appointments, route calls to the right departments, and even take messages — all with human-like conversational flow. The system is built on Python with FastAPI for the backend, integrated with Twilio for telephony, and uses OpenAI's Whisper for STT and ElevenLabs or Google TTS for lifelike voice responses. The NLU layer is powered by a fine-tuned BERT-based model for intent classification and entity extraction. I also built a dashboard (Streamlit/React) for business owners to view call logs, transcripts, and analytics. What makes it special: Human-like conversational AI with < 300ms response latency. Multi-language support (English, Spanish, French) with real-time switching. Intelligent call routing — identifies caller intent a

AI Voice Receptionist & Call Manager

Developed an intelligent AI voice receptionist system that automates incoming call management for businesses. The solution uses speech-to-text (STT) , natural language understanding (NLU) , and text-to-speech (TTS) to handle customer inquiries, schedule appointments, route calls to the right departments, and even take messages — all with human-like conversational flow. The system is built on Python with FastAPI for the backend, integrated with Twilio for telephony, and uses OpenAI's Whisper for STT and ElevenLabs or Google TTS for lifelike voice responses. The NLU layer is powered by a fine-tuned BERT-based model for intent classification and entity extraction. I also built a dashboard (Streamlit/React) for business owners to view call logs, transcripts, and analytics. What makes it special: Human-like conversational AI with < 300ms response latency. Multi-language support (English, Spanish, French) with real-time switching. Intelligent call routing — identifies caller intent a

AI Voice Receptionist & Call Manager

Developed an intelligent AI voice receptionist system that automates incoming call management for businesses. The solution uses speech-to-text (STT) , natural language understanding (NLU) , and text-to-speech (TTS) to handle customer inquiries, schedule appointments, route calls to the right departments, and even take messages — all with human-like conversational flow. The system is built on Python with FastAPI for the backend, integrated with Twilio for telephony, and uses OpenAI's Whisper for STT and ElevenLabs or Google TTS for lifelike voice responses. The NLU layer is powered by a fine-tuned BERT-based model for intent classification and entity extraction. I also built a dashboard (Streamlit/React) for business owners to view call logs, transcripts, and analytics. What makes it special: Human-like conversational AI with < 300ms response latency. Multi-language support (English, Spanish, French) with real-time switching. Intelligent call routing — identifies caller intent a

AI Voice Receptionist & Call Manager

Developed an intelligent AI voice receptionist system that automates incoming call management for businesses. The solution uses speech-to-text (STT) , natural language understanding (NLU) , and text-to-speech (TTS) to handle customer inquiries, schedule appointments, route calls to the right departments, and even take messages — all with human-like conversational flow. The system is built on Python with FastAPI for the backend, integrated with Twilio for telephony, and uses OpenAI's Whisper for STT and ElevenLabs or Google TTS for lifelike voice responses. The NLU layer is powered by a fine-tuned BERT-based model for intent classification and entity extraction. I also built a dashboard (Streamlit/React) for business owners to view call logs, transcripts, and analytics. What makes it special: Human-like conversational AI with < 300ms response latency. Multi-language support (English, Spanish, French) with real-time switching. Intelligent call routing — identifies caller intent a

AI Voice Receptionist & Call Manager

Developed an intelligent AI voice receptionist system that automates incoming call management for businesses. The solution uses speech-to-text (STT) , natural language understanding (NLU) , and text-to-speech (TTS) to handle customer inquiries, schedule appointments, route calls to the right departments, and even take messages — all with human-like conversational flow. The system is built on Python with FastAPI for the backend, integrated with Twilio for telephony, and uses OpenAI's Whisper for STT and ElevenLabs or Google TTS for lifelike voice responses. The NLU layer is powered by a fine-tuned BERT-based model for intent classification and entity extraction. I also built a dashboard (Streamlit/React) for business owners to view call logs, transcripts, and analytics. What makes it special: Human-like conversational AI with < 300ms response latency. Multi-language support (English, Spanish, French) with real-time switching. Intelligent call routing — identifies caller intent a

AI Voice Receptionist & Call Manager

Developed an intelligent AI voice receptionist system that automates incoming call management for businesses. The solution uses speech-to-text (STT) , natural language understanding (NLU) , and text-to-speech (TTS) to handle customer inquiries, schedule appointments, route calls to the right departments, and even take messages — all with human-like conversational flow. The system is built on Python with FastAPI for the backend, integrated with Twilio for telephony, and uses OpenAI's Whisper for STT and ElevenLabs or Google TTS for lifelike voice responses. The NLU layer is powered by a fine-tuned BERT-based model for intent classification and entity extraction. I also built a dashboard (Streamlit/React) for business owners to view call logs, transcripts, and analytics. What makes it special: Human-like conversational AI with < 300ms response latency. Multi-language support (English, Spanish, French) with real-time switching. Intelligent call routing — identifies caller intent a

AI Voice Receptionist & Call Manager

14001744
Developed a custom Shopify app that combines fashion and technology — allowing customers to predict upcoming fashion trends, vote on seasonal collections, and receive real-time "drop alerts" when predicted items become available for purchase. The app is seamlessly integrated into the Shopify storefront using Shopify's Storefront API and Hydrogen framework. It features a user dashboard where customers can track their prediction accuracy, earn loyalty points, and unlock exclusive early access to new collections. The backend is powered by Node.js with Firebase for real-time updates and push notifications. I also built a custom admin panel for store owners to manage trend campaigns, monitor user engagement, and automate alert scheduling based on inventory levels. What makes it special: Native Shopify login integration — no separate accounts needed. Real-time trend scoring based on user votes and purchase behavior. Automated "Season Alert" system — sends push/email

Fashionable Shopify Developement

Developed a custom Shopify app that combines fashion and technology — allowing customers to predict upcoming fashion trends, vote on seasonal collections, and receive real-time "drop alerts" when predicted items become available for purchase. The app is seamlessly integrated into the Shopify storefront using Shopify's Storefront API and Hydrogen framework. It features a user dashboard where customers can track their prediction accuracy, earn loyalty points, and unlock exclusive early access to new collections. The backend is powered by Node.js with Firebase for real-time updates and push notifications. I also built a custom admin panel for store owners to manage trend campaigns, monitor user engagement, and automate alert scheduling based on inventory levels. What makes it special: Native Shopify login integration — no separate accounts needed. Real-time trend scoring based on user votes and purchase behavior. Automated "Season Alert" system — sends push/email

Fashionable Shopify Developement

Developed a custom Shopify app that combines fashion and technology — allowing customers to predict upcoming fashion trends, vote on seasonal collections, and receive real-time "drop alerts" when predicted items become available for purchase. The app is seamlessly integrated into the Shopify storefront using Shopify's Storefront API and Hydrogen framework. It features a user dashboard where customers can track their prediction accuracy, earn loyalty points, and unlock exclusive early access to new collections. The backend is powered by Node.js with Firebase for real-time updates and push notifications. I also built a custom admin panel for store owners to manage trend campaigns, monitor user engagement, and automate alert scheduling based on inventory levels. What makes it special: Native Shopify login integration — no separate accounts needed. Real-time trend scoring based on user votes and purchase behavior. Automated "Season Alert" system — sends push/email

Fashionable Shopify Developement

Developed a custom Shopify app that combines fashion and technology — allowing customers to predict upcoming fashion trends, vote on seasonal collections, and receive real-time "drop alerts" when predicted items become available for purchase. The app is seamlessly integrated into the Shopify storefront using Shopify's Storefront API and Hydrogen framework. It features a user dashboard where customers can track their prediction accuracy, earn loyalty points, and unlock exclusive early access to new collections. The backend is powered by Node.js with Firebase for real-time updates and push notifications. I also built a custom admin panel for store owners to manage trend campaigns, monitor user engagement, and automate alert scheduling based on inventory levels. What makes it special: Native Shopify login integration — no separate accounts needed. Real-time trend scoring based on user votes and purchase behavior. Automated "Season Alert" system — sends push/email

Fashionable Shopify Developement

Developed a custom Shopify app that combines fashion and technology — allowing customers to predict upcoming fashion trends, vote on seasonal collections, and receive real-time "drop alerts" when predicted items become available for purchase. The app is seamlessly integrated into the Shopify storefront using Shopify's Storefront API and Hydrogen framework. It features a user dashboard where customers can track their prediction accuracy, earn loyalty points, and unlock exclusive early access to new collections. The backend is powered by Node.js with Firebase for real-time updates and push notifications. I also built a custom admin panel for store owners to manage trend campaigns, monitor user engagement, and automate alert scheduling based on inventory levels. What makes it special: Native Shopify login integration — no separate accounts needed. Real-time trend scoring based on user votes and purchase behavior. Automated "Season Alert" system — sends push/email

Fashionable Shopify Developement

14001731
Built a cross-platform mobile app (iOS & Android) for tech enthusiasts to predict upcoming gadget launches, product specs, and market trends. Users can vote on rumored features, earn accuracy scores, and climb global leaderboards. The "Tech Alert" system delivers smart notifications for product announcements, price drops, and when a user's prediction is confirmed by official releases. Technical stack: Built with React Native for native-like performance, Firebase for real-time sync and authentication, and integrated with tech news APIs and product databases (e.g., Best Buy, Amazon) for live pricing and availability. The app also includes a dark-mode interface optimized for tech-savvy users. What makes it special: Real-time prediction scoring based on actual product announcements. Smart alert engine with customizable notification preferences. Integrated with live product feeds for instant price/spec updates. Gamified experience with badges, streaks, and seasonal chall

Tech Gadget Predictor & Alert App

Built a cross-platform mobile app (iOS & Android) for tech enthusiasts to predict upcoming gadget launches, product specs, and market trends. Users can vote on rumored features, earn accuracy scores, and climb global leaderboards. The "Tech Alert" system delivers smart notifications for product announcements, price drops, and when a user's prediction is confirmed by official releases. Technical stack: Built with React Native for native-like performance, Firebase for real-time sync and authentication, and integrated with tech news APIs and product databases (e.g., Best Buy, Amazon) for live pricing and availability. The app also includes a dark-mode interface optimized for tech-savvy users. What makes it special: Real-time prediction scoring based on actual product announcements. Smart alert engine with customizable notification preferences. Integrated with live product feeds for instant price/spec updates. Gamified experience with badges, streaks, and seasonal chall

Tech Gadget Predictor & Alert App

Built a cross-platform mobile app (iOS & Android) for tech enthusiasts to predict upcoming gadget launches, product specs, and market trends. Users can vote on rumored features, earn accuracy scores, and climb global leaderboards. The "Tech Alert" system delivers smart notifications for product announcements, price drops, and when a user's prediction is confirmed by official releases. Technical stack: Built with React Native for native-like performance, Firebase for real-time sync and authentication, and integrated with tech news APIs and product databases (e.g., Best Buy, Amazon) for live pricing and availability. The app also includes a dark-mode interface optimized for tech-savvy users. What makes it special: Real-time prediction scoring based on actual product announcements. Smart alert engine with customizable notification preferences. Integrated with live product feeds for instant price/spec updates. Gamified experience with badges, streaks, and seasonal chall

Tech Gadget Predictor & Alert App

Built a cross-platform mobile app (iOS & Android) for tech enthusiasts to predict upcoming gadget launches, product specs, and market trends. Users can vote on rumored features, earn accuracy scores, and climb global leaderboards. The "Tech Alert" system delivers smart notifications for product announcements, price drops, and when a user's prediction is confirmed by official releases. Technical stack: Built with React Native for native-like performance, Firebase for real-time sync and authentication, and integrated with tech news APIs and product databases (e.g., Best Buy, Amazon) for live pricing and availability. The app also includes a dark-mode interface optimized for tech-savvy users. What makes it special: Real-time prediction scoring based on actual product announcements. Smart alert engine with customizable notification preferences. Integrated with live product feeds for instant price/spec updates. Gamified experience with badges, streaks, and seasonal chall

Tech Gadget Predictor & Alert App

Built a cross-platform mobile app (iOS & Android) for tech enthusiasts to predict upcoming gadget launches, product specs, and market trends. Users can vote on rumored features, earn accuracy scores, and climb global leaderboards. The "Tech Alert" system delivers smart notifications for product announcements, price drops, and when a user's prediction is confirmed by official releases. Technical stack: Built with React Native for native-like performance, Firebase for real-time sync and authentication, and integrated with tech news APIs and product databases (e.g., Best Buy, Amazon) for live pricing and availability. The app also includes a dark-mode interface optimized for tech-savvy users. What makes it special: Real-time prediction scoring based on actual product announcements. Smart alert engine with customizable notification preferences. Integrated with live product feeds for instant price/spec updates. Gamified experience with badges, streaks, and seasonal chall

Tech Gadget Predictor & Alert App

Built a cross-platform mobile app (iOS & Android) for tech enthusiasts to predict upcoming gadget launches, product specs, and market trends. Users can vote on rumored features, earn accuracy scores, and climb global leaderboards. The "Tech Alert" system delivers smart notifications for product announcements, price drops, and when a user's prediction is confirmed by official releases. Technical stack: Built with React Native for native-like performance, Firebase for real-time sync and authentication, and integrated with tech news APIs and product databases (e.g., Best Buy, Amazon) for live pricing and availability. The app also includes a dark-mode interface optimized for tech-savvy users. What makes it special: Real-time prediction scoring based on actual product announcements. Smart alert engine with customizable notification preferences. Integrated with live product feeds for instant price/spec updates. Gamified experience with badges, streaks, and seasonal chall

Tech Gadget Predictor & Alert App

14001714
Developed an end-to-end AI solution that processes live customer feedback across multiple channels (chat, email, social media) and classifies sentiment with 92% accuracy. The system uses a fine-tuned transformer model (DistilBERT) deployed via FastAPI on AWS Lambda, with real-time dashboards built using Streamlit. I also designed the data ingestion layer, implemented drift detection, and set up CI/CD for model retraining. What makes it special: Achieved sub-200ms inference latency at scale. Built a custom active learning loop to continuously improve on edge cases. Integrated explainability (SHAP) to provide actionable insights to business teams. Reduced manual moderation effort by 70% for the client.

Real-Time NLP Sentiment API on AWS

Developed an end-to-end AI solution that processes live customer feedback across multiple channels (chat, email, social media) and classifies sentiment with 92% accuracy. The system uses a fine-tuned transformer model (DistilBERT) deployed via FastAPI on AWS Lambda, with real-time dashboards built using Streamlit. I also designed the data ingestion layer, implemented drift detection, and set up CI/CD for model retraining. What makes it special: Achieved sub-200ms inference latency at scale. Built a custom active learning loop to continuously improve on edge cases. Integrated explainability (SHAP) to provide actionable insights to business teams. Reduced manual moderation effort by 70% for the client.

Real-Time NLP Sentiment API on AWS

Developed an end-to-end AI solution that processes live customer feedback across multiple channels (chat, email, social media) and classifies sentiment with 92% accuracy. The system uses a fine-tuned transformer model (DistilBERT) deployed via FastAPI on AWS Lambda, with real-time dashboards built using Streamlit. I also designed the data ingestion layer, implemented drift detection, and set up CI/CD for model retraining. What makes it special: Achieved sub-200ms inference latency at scale. Built a custom active learning loop to continuously improve on edge cases. Integrated explainability (SHAP) to provide actionable insights to business teams. Reduced manual moderation effort by 70% for the client.

Real-Time NLP Sentiment API on AWS

Developed an end-to-end AI solution that processes live customer feedback across multiple channels (chat, email, social media) and classifies sentiment with 92% accuracy. The system uses a fine-tuned transformer model (DistilBERT) deployed via FastAPI on AWS Lambda, with real-time dashboards built using Streamlit. I also designed the data ingestion layer, implemented drift detection, and set up CI/CD for model retraining. What makes it special: Achieved sub-200ms inference latency at scale. Built a custom active learning loop to continuously improve on edge cases. Integrated explainability (SHAP) to provide actionable insights to business teams. Reduced manual moderation effort by 70% for the client.

Real-Time NLP Sentiment API on AWS

Developed an end-to-end AI solution that processes live customer feedback across multiple channels (chat, email, social media) and classifies sentiment with 92% accuracy. The system uses a fine-tuned transformer model (DistilBERT) deployed via FastAPI on AWS Lambda, with real-time dashboards built using Streamlit. I also designed the data ingestion layer, implemented drift detection, and set up CI/CD for model retraining. What makes it special: Achieved sub-200ms inference latency at scale. Built a custom active learning loop to continuously improve on edge cases. Integrated explainability (SHAP) to provide actionable insights to business teams. Reduced manual moderation effort by 70% for the client.

Real-Time NLP Sentiment API on AWS

Developed an end-to-end AI solution that processes live customer feedback across multiple channels (chat, email, social media) and classifies sentiment with 92% accuracy. The system uses a fine-tuned transformer model (DistilBERT) deployed via FastAPI on AWS Lambda, with real-time dashboards built using Streamlit. I also designed the data ingestion layer, implemented drift detection, and set up CI/CD for model retraining. What makes it special: Achieved sub-200ms inference latency at scale. Built a custom active learning loop to continuously improve on edge cases. Integrated explainability (SHAP) to provide actionable insights to business teams. Reduced manual moderation effort by 70% for the client.

Real-Time NLP Sentiment API on AWS

14001775
Developed a custom Shopify app that notifies customers the moment their favorite products drop in price, come back in stock, or launch as new collections. The app integrates seamlessly with the Shopify storefront using the Storefront API and Webhooks for real-time inventory and price tracking. Users can "watch" products with a single tap, set custom alert preferences (price threshold, stock status, or new arrivals), and receive instant notifications via email, SMS, or push notifications (on mobile). The app also includes a personalized dashboard where customers can manage their watched items and view alert history. Technical stack: Built with Node.js and Express for the backend, Shopify Polaris for the admin panel, and Firebase Cloud Messaging for push notifications. The frontend uses React with Hydrogen for a blazing-fast storefront experience. I also implemented Redis for caching to handle high-traffic events like flash sales. What makes it special: Real-time price and

Drop Alert - Shopify Shopper

Developed a custom Shopify app that notifies customers the moment their favorite products drop in price, come back in stock, or launch as new collections. The app integrates seamlessly with the Shopify storefront using the Storefront API and Webhooks for real-time inventory and price tracking. Users can "watch" products with a single tap, set custom alert preferences (price threshold, stock status, or new arrivals), and receive instant notifications via email, SMS, or push notifications (on mobile). The app also includes a personalized dashboard where customers can manage their watched items and view alert history. Technical stack: Built with Node.js and Express for the backend, Shopify Polaris for the admin panel, and Firebase Cloud Messaging for push notifications. The frontend uses React with Hydrogen for a blazing-fast storefront experience. I also implemented Redis for caching to handle high-traffic events like flash sales. What makes it special: Real-time price and

Drop Alert - Shopify Shopper

Developed a custom Shopify app that notifies customers the moment their favorite products drop in price, come back in stock, or launch as new collections. The app integrates seamlessly with the Shopify storefront using the Storefront API and Webhooks for real-time inventory and price tracking. Users can "watch" products with a single tap, set custom alert preferences (price threshold, stock status, or new arrivals), and receive instant notifications via email, SMS, or push notifications (on mobile). The app also includes a personalized dashboard where customers can manage their watched items and view alert history. Technical stack: Built with Node.js and Express for the backend, Shopify Polaris for the admin panel, and Firebase Cloud Messaging for push notifications. The frontend uses React with Hydrogen for a blazing-fast storefront experience. I also implemented Redis for caching to handle high-traffic events like flash sales. What makes it special: Real-time price and

Drop Alert - Shopify Shopper

Developed a custom Shopify app that notifies customers the moment their favorite products drop in price, come back in stock, or launch as new collections. The app integrates seamlessly with the Shopify storefront using the Storefront API and Webhooks for real-time inventory and price tracking. Users can "watch" products with a single tap, set custom alert preferences (price threshold, stock status, or new arrivals), and receive instant notifications via email, SMS, or push notifications (on mobile). The app also includes a personalized dashboard where customers can manage their watched items and view alert history. Technical stack: Built with Node.js and Express for the backend, Shopify Polaris for the admin panel, and Firebase Cloud Messaging for push notifications. The frontend uses React with Hydrogen for a blazing-fast storefront experience. I also implemented Redis for caching to handle high-traffic events like flash sales. What makes it special: Real-time price and

Drop Alert - Shopify Shopper

Developed a custom Shopify app that notifies customers the moment their favorite products drop in price, come back in stock, or launch as new collections. The app integrates seamlessly with the Shopify storefront using the Storefront API and Webhooks for real-time inventory and price tracking. Users can "watch" products with a single tap, set custom alert preferences (price threshold, stock status, or new arrivals), and receive instant notifications via email, SMS, or push notifications (on mobile). The app also includes a personalized dashboard where customers can manage their watched items and view alert history. Technical stack: Built with Node.js and Express for the backend, Shopify Polaris for the admin panel, and Firebase Cloud Messaging for push notifications. The frontend uses React with Hydrogen for a blazing-fast storefront experience. I also implemented Redis for caching to handle high-traffic events like flash sales. What makes it special: Real-time price and

Drop Alert - Shopify Shopper

14001761
Developed a cross-platform mobile app (iOS & Android) that turns any smartphone into an intelligent AI voice receptionist. The app allows business owners to manage incoming calls, schedule appointments, and handle customer inquiries — all from their mobile device, even when away from the office. The app connects to a cloud-based AI backend that processes calls using speech-to-text, natural language understanding, and text-to-speech. Users can view real-time call transcripts, listen to voicemail summaries, respond via chat or voice, and manage their availability — all through an intuitive, native-feeling mobile interface. Technical stack: Built with Flutter for cross-platform performance, Firebase for real-time sync and push notifications, and integrated with Twilio's Voice API for call handling. The app also features a beautiful, minimal dashboard with call analytics, sentiment insights, and calendar sync. What makes it special: Native-quality UI with smooth animations and gest

Smart Gadget Predictor Apps

Developed a cross-platform mobile app (iOS & Android) that turns any smartphone into an intelligent AI voice receptionist. The app allows business owners to manage incoming calls, schedule appointments, and handle customer inquiries — all from their mobile device, even when away from the office. The app connects to a cloud-based AI backend that processes calls using speech-to-text, natural language understanding, and text-to-speech. Users can view real-time call transcripts, listen to voicemail summaries, respond via chat or voice, and manage their availability — all through an intuitive, native-feeling mobile interface. Technical stack: Built with Flutter for cross-platform performance, Firebase for real-time sync and push notifications, and integrated with Twilio's Voice API for call handling. The app also features a beautiful, minimal dashboard with call analytics, sentiment insights, and calendar sync. What makes it special: Native-quality UI with smooth animations and gest

Smart Gadget Predictor Apps

Developed a cross-platform mobile app (iOS & Android) that turns any smartphone into an intelligent AI voice receptionist. The app allows business owners to manage incoming calls, schedule appointments, and handle customer inquiries — all from their mobile device, even when away from the office. The app connects to a cloud-based AI backend that processes calls using speech-to-text, natural language understanding, and text-to-speech. Users can view real-time call transcripts, listen to voicemail summaries, respond via chat or voice, and manage their availability — all through an intuitive, native-feeling mobile interface. Technical stack: Built with Flutter for cross-platform performance, Firebase for real-time sync and push notifications, and integrated with Twilio's Voice API for call handling. The app also features a beautiful, minimal dashboard with call analytics, sentiment insights, and calendar sync. What makes it special: Native-quality UI with smooth animations and gest

Smart Gadget Predictor Apps

Developed a cross-platform mobile app (iOS & Android) that turns any smartphone into an intelligent AI voice receptionist. The app allows business owners to manage incoming calls, schedule appointments, and handle customer inquiries — all from their mobile device, even when away from the office. The app connects to a cloud-based AI backend that processes calls using speech-to-text, natural language understanding, and text-to-speech. Users can view real-time call transcripts, listen to voicemail summaries, respond via chat or voice, and manage their availability — all through an intuitive, native-feeling mobile interface. Technical stack: Built with Flutter for cross-platform performance, Firebase for real-time sync and push notifications, and integrated with Twilio's Voice API for call handling. The app also features a beautiful, minimal dashboard with call analytics, sentiment insights, and calendar sync. What makes it special: Native-quality UI with smooth animations and gest

Smart Gadget Predictor Apps

Developed a cross-platform mobile app (iOS & Android) that turns any smartphone into an intelligent AI voice receptionist. The app allows business owners to manage incoming calls, schedule appointments, and handle customer inquiries — all from their mobile device, even when away from the office. The app connects to a cloud-based AI backend that processes calls using speech-to-text, natural language understanding, and text-to-speech. Users can view real-time call transcripts, listen to voicemail summaries, respond via chat or voice, and manage their availability — all through an intuitive, native-feeling mobile interface. Technical stack: Built with Flutter for cross-platform performance, Firebase for real-time sync and push notifications, and integrated with Twilio's Voice API for call handling. The app also features a beautiful, minimal dashboard with call analytics, sentiment insights, and calendar sync. What makes it special: Native-quality UI with smooth animations and gest

Smart Gadget Predictor Apps

14001751
Developed an intelligent AI voice receptionist system that automates incoming call management for businesses. The solution uses speech-to-text (STT) , natural language understanding (NLU) , and text-to-speech (TTS) to handle customer inquiries, schedule appointments, route calls to the right departments, and even take messages — all with human-like conversational flow. The system is built on Python with FastAPI for the backend, integrated with Twilio for telephony, and uses OpenAI's Whisper for STT and ElevenLabs or Google TTS for lifelike voice responses. The NLU layer is powered by a fine-tuned BERT-based model for intent classification and entity extraction. I also built a dashboard (Streamlit/React) for business owners to view call logs, transcripts, and analytics. What makes it special: Human-like conversational AI with < 300ms response latency. Multi-language support (English, Spanish, French) with real-time switching. Intelligent call routing — identifies caller intent a

AI Voice Receptionist & Call Manager

Developed an intelligent AI voice receptionist system that automates incoming call management for businesses. The solution uses speech-to-text (STT) , natural language understanding (NLU) , and text-to-speech (TTS) to handle customer inquiries, schedule appointments, route calls to the right departments, and even take messages — all with human-like conversational flow. The system is built on Python with FastAPI for the backend, integrated with Twilio for telephony, and uses OpenAI's Whisper for STT and ElevenLabs or Google TTS for lifelike voice responses. The NLU layer is powered by a fine-tuned BERT-based model for intent classification and entity extraction. I also built a dashboard (Streamlit/React) for business owners to view call logs, transcripts, and analytics. What makes it special: Human-like conversational AI with < 300ms response latency. Multi-language support (English, Spanish, French) with real-time switching. Intelligent call routing — identifies caller intent a

AI Voice Receptionist & Call Manager

Developed an intelligent AI voice receptionist system that automates incoming call management for businesses. The solution uses speech-to-text (STT) , natural language understanding (NLU) , and text-to-speech (TTS) to handle customer inquiries, schedule appointments, route calls to the right departments, and even take messages — all with human-like conversational flow. The system is built on Python with FastAPI for the backend, integrated with Twilio for telephony, and uses OpenAI's Whisper for STT and ElevenLabs or Google TTS for lifelike voice responses. The NLU layer is powered by a fine-tuned BERT-based model for intent classification and entity extraction. I also built a dashboard (Streamlit/React) for business owners to view call logs, transcripts, and analytics. What makes it special: Human-like conversational AI with < 300ms response latency. Multi-language support (English, Spanish, French) with real-time switching. Intelligent call routing — identifies caller intent a

AI Voice Receptionist & Call Manager

Developed an intelligent AI voice receptionist system that automates incoming call management for businesses. The solution uses speech-to-text (STT) , natural language understanding (NLU) , and text-to-speech (TTS) to handle customer inquiries, schedule appointments, route calls to the right departments, and even take messages — all with human-like conversational flow. The system is built on Python with FastAPI for the backend, integrated with Twilio for telephony, and uses OpenAI's Whisper for STT and ElevenLabs or Google TTS for lifelike voice responses. The NLU layer is powered by a fine-tuned BERT-based model for intent classification and entity extraction. I also built a dashboard (Streamlit/React) for business owners to view call logs, transcripts, and analytics. What makes it special: Human-like conversational AI with < 300ms response latency. Multi-language support (English, Spanish, French) with real-time switching. Intelligent call routing — identifies caller intent a

AI Voice Receptionist & Call Manager

Developed an intelligent AI voice receptionist system that automates incoming call management for businesses. The solution uses speech-to-text (STT) , natural language understanding (NLU) , and text-to-speech (TTS) to handle customer inquiries, schedule appointments, route calls to the right departments, and even take messages — all with human-like conversational flow. The system is built on Python with FastAPI for the backend, integrated with Twilio for telephony, and uses OpenAI's Whisper for STT and ElevenLabs or Google TTS for lifelike voice responses. The NLU layer is powered by a fine-tuned BERT-based model for intent classification and entity extraction. I also built a dashboard (Streamlit/React) for business owners to view call logs, transcripts, and analytics. What makes it special: Human-like conversational AI with < 300ms response latency. Multi-language support (English, Spanish, French) with real-time switching. Intelligent call routing — identifies caller intent a

AI Voice Receptionist & Call Manager

Developed an intelligent AI voice receptionist system that automates incoming call management for businesses. The solution uses speech-to-text (STT) , natural language understanding (NLU) , and text-to-speech (TTS) to handle customer inquiries, schedule appointments, route calls to the right departments, and even take messages — all with human-like conversational flow. The system is built on Python with FastAPI for the backend, integrated with Twilio for telephony, and uses OpenAI's Whisper for STT and ElevenLabs or Google TTS for lifelike voice responses. The NLU layer is powered by a fine-tuned BERT-based model for intent classification and entity extraction. I also built a dashboard (Streamlit/React) for business owners to view call logs, transcripts, and analytics. What makes it special: Human-like conversational AI with < 300ms response latency. Multi-language support (English, Spanish, French) with real-time switching. Intelligent call routing — identifies caller intent a

AI Voice Receptionist & Call Manager

Developed an intelligent AI voice receptionist system that automates incoming call management for businesses. The solution uses speech-to-text (STT) , natural language understanding (NLU) , and text-to-speech (TTS) to handle customer inquiries, schedule appointments, route calls to the right departments, and even take messages — all with human-like conversational flow. The system is built on Python with FastAPI for the backend, integrated with Twilio for telephony, and uses OpenAI's Whisper for STT and ElevenLabs or Google TTS for lifelike voice responses. The NLU layer is powered by a fine-tuned BERT-based model for intent classification and entity extraction. I also built a dashboard (Streamlit/React) for business owners to view call logs, transcripts, and analytics. What makes it special: Human-like conversational AI with < 300ms response latency. Multi-language support (English, Spanish, French) with real-time switching. Intelligent call routing — identifies caller intent a

AI Voice Receptionist & Call Manager

14001744
Developed a custom Shopify app that combines fashion and technology — allowing customers to predict upcoming fashion trends, vote on seasonal collections, and receive real-time "drop alerts" when predicted items become available for purchase. The app is seamlessly integrated into the Shopify storefront using Shopify's Storefront API and Hydrogen framework. It features a user dashboard where customers can track their prediction accuracy, earn loyalty points, and unlock exclusive early access to new collections. The backend is powered by Node.js with Firebase for real-time updates and push notifications. I also built a custom admin panel for store owners to manage trend campaigns, monitor user engagement, and automate alert scheduling based on inventory levels. What makes it special: Native Shopify login integration — no separate accounts needed. Real-time trend scoring based on user votes and purchase behavior. Automated "Season Alert" system — sends push/email

Fashionable Shopify Developement

Developed a custom Shopify app that combines fashion and technology — allowing customers to predict upcoming fashion trends, vote on seasonal collections, and receive real-time "drop alerts" when predicted items become available for purchase. The app is seamlessly integrated into the Shopify storefront using Shopify's Storefront API and Hydrogen framework. It features a user dashboard where customers can track their prediction accuracy, earn loyalty points, and unlock exclusive early access to new collections. The backend is powered by Node.js with Firebase for real-time updates and push notifications. I also built a custom admin panel for store owners to manage trend campaigns, monitor user engagement, and automate alert scheduling based on inventory levels. What makes it special: Native Shopify login integration — no separate accounts needed. Real-time trend scoring based on user votes and purchase behavior. Automated "Season Alert" system — sends push/email

Fashionable Shopify Developement

Developed a custom Shopify app that combines fashion and technology — allowing customers to predict upcoming fashion trends, vote on seasonal collections, and receive real-time "drop alerts" when predicted items become available for purchase. The app is seamlessly integrated into the Shopify storefront using Shopify's Storefront API and Hydrogen framework. It features a user dashboard where customers can track their prediction accuracy, earn loyalty points, and unlock exclusive early access to new collections. The backend is powered by Node.js with Firebase for real-time updates and push notifications. I also built a custom admin panel for store owners to manage trend campaigns, monitor user engagement, and automate alert scheduling based on inventory levels. What makes it special: Native Shopify login integration — no separate accounts needed. Real-time trend scoring based on user votes and purchase behavior. Automated "Season Alert" system — sends push/email

Fashionable Shopify Developement

Developed a custom Shopify app that combines fashion and technology — allowing customers to predict upcoming fashion trends, vote on seasonal collections, and receive real-time "drop alerts" when predicted items become available for purchase. The app is seamlessly integrated into the Shopify storefront using Shopify's Storefront API and Hydrogen framework. It features a user dashboard where customers can track their prediction accuracy, earn loyalty points, and unlock exclusive early access to new collections. The backend is powered by Node.js with Firebase for real-time updates and push notifications. I also built a custom admin panel for store owners to manage trend campaigns, monitor user engagement, and automate alert scheduling based on inventory levels. What makes it special: Native Shopify login integration — no separate accounts needed. Real-time trend scoring based on user votes and purchase behavior. Automated "Season Alert" system — sends push/email

Fashionable Shopify Developement

Developed a custom Shopify app that combines fashion and technology — allowing customers to predict upcoming fashion trends, vote on seasonal collections, and receive real-time "drop alerts" when predicted items become available for purchase. The app is seamlessly integrated into the Shopify storefront using Shopify's Storefront API and Hydrogen framework. It features a user dashboard where customers can track their prediction accuracy, earn loyalty points, and unlock exclusive early access to new collections. The backend is powered by Node.js with Firebase for real-time updates and push notifications. I also built a custom admin panel for store owners to manage trend campaigns, monitor user engagement, and automate alert scheduling based on inventory levels. What makes it special: Native Shopify login integration — no separate accounts needed. Real-time trend scoring based on user votes and purchase behavior. Automated "Season Alert" system — sends push/email

Fashionable Shopify Developement

14001731
Built a cross-platform mobile app (iOS & Android) for tech enthusiasts to predict upcoming gadget launches, product specs, and market trends. Users can vote on rumored features, earn accuracy scores, and climb global leaderboards. The "Tech Alert" system delivers smart notifications for product announcements, price drops, and when a user's prediction is confirmed by official releases. Technical stack: Built with React Native for native-like performance, Firebase for real-time sync and authentication, and integrated with tech news APIs and product databases (e.g., Best Buy, Amazon) for live pricing and availability. The app also includes a dark-mode interface optimized for tech-savvy users. What makes it special: Real-time prediction scoring based on actual product announcements. Smart alert engine with customizable notification preferences. Integrated with live product feeds for instant price/spec updates. Gamified experience with badges, streaks, and seasonal chall

Tech Gadget Predictor & Alert App

Built a cross-platform mobile app (iOS & Android) for tech enthusiasts to predict upcoming gadget launches, product specs, and market trends. Users can vote on rumored features, earn accuracy scores, and climb global leaderboards. The "Tech Alert" system delivers smart notifications for product announcements, price drops, and when a user's prediction is confirmed by official releases. Technical stack: Built with React Native for native-like performance, Firebase for real-time sync and authentication, and integrated with tech news APIs and product databases (e.g., Best Buy, Amazon) for live pricing and availability. The app also includes a dark-mode interface optimized for tech-savvy users. What makes it special: Real-time prediction scoring based on actual product announcements. Smart alert engine with customizable notification preferences. Integrated with live product feeds for instant price/spec updates. Gamified experience with badges, streaks, and seasonal chall

Tech Gadget Predictor & Alert App

Built a cross-platform mobile app (iOS & Android) for tech enthusiasts to predict upcoming gadget launches, product specs, and market trends. Users can vote on rumored features, earn accuracy scores, and climb global leaderboards. The "Tech Alert" system delivers smart notifications for product announcements, price drops, and when a user's prediction is confirmed by official releases. Technical stack: Built with React Native for native-like performance, Firebase for real-time sync and authentication, and integrated with tech news APIs and product databases (e.g., Best Buy, Amazon) for live pricing and availability. The app also includes a dark-mode interface optimized for tech-savvy users. What makes it special: Real-time prediction scoring based on actual product announcements. Smart alert engine with customizable notification preferences. Integrated with live product feeds for instant price/spec updates. Gamified experience with badges, streaks, and seasonal chall

Tech Gadget Predictor & Alert App

Built a cross-platform mobile app (iOS & Android) for tech enthusiasts to predict upcoming gadget launches, product specs, and market trends. Users can vote on rumored features, earn accuracy scores, and climb global leaderboards. The "Tech Alert" system delivers smart notifications for product announcements, price drops, and when a user's prediction is confirmed by official releases. Technical stack: Built with React Native for native-like performance, Firebase for real-time sync and authentication, and integrated with tech news APIs and product databases (e.g., Best Buy, Amazon) for live pricing and availability. The app also includes a dark-mode interface optimized for tech-savvy users. What makes it special: Real-time prediction scoring based on actual product announcements. Smart alert engine with customizable notification preferences. Integrated with live product feeds for instant price/spec updates. Gamified experience with badges, streaks, and seasonal chall

Tech Gadget Predictor & Alert App

Built a cross-platform mobile app (iOS & Android) for tech enthusiasts to predict upcoming gadget launches, product specs, and market trends. Users can vote on rumored features, earn accuracy scores, and climb global leaderboards. The "Tech Alert" system delivers smart notifications for product announcements, price drops, and when a user's prediction is confirmed by official releases. Technical stack: Built with React Native for native-like performance, Firebase for real-time sync and authentication, and integrated with tech news APIs and product databases (e.g., Best Buy, Amazon) for live pricing and availability. The app also includes a dark-mode interface optimized for tech-savvy users. What makes it special: Real-time prediction scoring based on actual product announcements. Smart alert engine with customizable notification preferences. Integrated with live product feeds for instant price/spec updates. Gamified experience with badges, streaks, and seasonal chall

Tech Gadget Predictor & Alert App

Built a cross-platform mobile app (iOS & Android) for tech enthusiasts to predict upcoming gadget launches, product specs, and market trends. Users can vote on rumored features, earn accuracy scores, and climb global leaderboards. The "Tech Alert" system delivers smart notifications for product announcements, price drops, and when a user's prediction is confirmed by official releases. Technical stack: Built with React Native for native-like performance, Firebase for real-time sync and authentication, and integrated with tech news APIs and product databases (e.g., Best Buy, Amazon) for live pricing and availability. The app also includes a dark-mode interface optimized for tech-savvy users. What makes it special: Real-time prediction scoring based on actual product announcements. Smart alert engine with customizable notification preferences. Integrated with live product feeds for instant price/spec updates. Gamified experience with badges, streaks, and seasonal chall

Tech Gadget Predictor & Alert App

14001714
Developed an end-to-end AI solution that processes live customer feedback across multiple channels (chat, email, social media) and classifies sentiment with 92% accuracy. The system uses a fine-tuned transformer model (DistilBERT) deployed via FastAPI on AWS Lambda, with real-time dashboards built using Streamlit. I also designed the data ingestion layer, implemented drift detection, and set up CI/CD for model retraining. What makes it special: Achieved sub-200ms inference latency at scale. Built a custom active learning loop to continuously improve on edge cases. Integrated explainability (SHAP) to provide actionable insights to business teams. Reduced manual moderation effort by 70% for the client.

Real-Time NLP Sentiment API on AWS

Developed an end-to-end AI solution that processes live customer feedback across multiple channels (chat, email, social media) and classifies sentiment with 92% accuracy. The system uses a fine-tuned transformer model (DistilBERT) deployed via FastAPI on AWS Lambda, with real-time dashboards built using Streamlit. I also designed the data ingestion layer, implemented drift detection, and set up CI/CD for model retraining. What makes it special: Achieved sub-200ms inference latency at scale. Built a custom active learning loop to continuously improve on edge cases. Integrated explainability (SHAP) to provide actionable insights to business teams. Reduced manual moderation effort by 70% for the client.

Real-Time NLP Sentiment API on AWS

Developed an end-to-end AI solution that processes live customer feedback across multiple channels (chat, email, social media) and classifies sentiment with 92% accuracy. The system uses a fine-tuned transformer model (DistilBERT) deployed via FastAPI on AWS Lambda, with real-time dashboards built using Streamlit. I also designed the data ingestion layer, implemented drift detection, and set up CI/CD for model retraining. What makes it special: Achieved sub-200ms inference latency at scale. Built a custom active learning loop to continuously improve on edge cases. Integrated explainability (SHAP) to provide actionable insights to business teams. Reduced manual moderation effort by 70% for the client.

Real-Time NLP Sentiment API on AWS

Developed an end-to-end AI solution that processes live customer feedback across multiple channels (chat, email, social media) and classifies sentiment with 92% accuracy. The system uses a fine-tuned transformer model (DistilBERT) deployed via FastAPI on AWS Lambda, with real-time dashboards built using Streamlit. I also designed the data ingestion layer, implemented drift detection, and set up CI/CD for model retraining. What makes it special: Achieved sub-200ms inference latency at scale. Built a custom active learning loop to continuously improve on edge cases. Integrated explainability (SHAP) to provide actionable insights to business teams. Reduced manual moderation effort by 70% for the client.

Real-Time NLP Sentiment API on AWS

Developed an end-to-end AI solution that processes live customer feedback across multiple channels (chat, email, social media) and classifies sentiment with 92% accuracy. The system uses a fine-tuned transformer model (DistilBERT) deployed via FastAPI on AWS Lambda, with real-time dashboards built using Streamlit. I also designed the data ingestion layer, implemented drift detection, and set up CI/CD for model retraining. What makes it special: Achieved sub-200ms inference latency at scale. Built a custom active learning loop to continuously improve on edge cases. Integrated explainability (SHAP) to provide actionable insights to business teams. Reduced manual moderation effort by 70% for the client.

Real-Time NLP Sentiment API on AWS

Developed an end-to-end AI solution that processes live customer feedback across multiple channels (chat, email, social media) and classifies sentiment with 92% accuracy. The system uses a fine-tuned transformer model (DistilBERT) deployed via FastAPI on AWS Lambda, with real-time dashboards built using Streamlit. I also designed the data ingestion layer, implemented drift detection, and set up CI/CD for model retraining. What makes it special: Achieved sub-200ms inference latency at scale. Built a custom active learning loop to continuously improve on edge cases. Integrated explainability (SHAP) to provide actionable insights to business teams. Reduced manual moderation effort by 70% for the client.

Real-Time NLP Sentiment API on AWS

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Experience

Full stack Shopify Lead

Aug, 2024 - May, 2026

•

1 year, 9 months

Shopware & Co. Digital GmbH

Aug, 2024 - May, 2026

•

1 year, 9 months

Led end-to-end Shopify Plus development using Liquid, React (Next.js), and Node.js. Built custom apps, checkout extensions, and headless storefronts. Managed a team of 8, conducted code reviews, and optimized site speed by 45%. Integrated ERP, payment, and third-party APIs. Improved conversion rate by 20% through UX/UI enhancements.

Flag of GERMANY

Hamburg, Germany

Aug, 2024 - May, 2026

•

1 year, 9 months

Full stack AI Engineer

Oct, 2021 - Jul, 2024

•

2 years, 9 months

Klavis.ai GmbH

Oct, 2021 - Jul, 2024

•

2 years, 9 months

Designed and deployed NLP and CV models using PyTorch and TensorFlow. Built MLOps pipelines on AWS with Docker and Kubernetes. Implemented RAG systems using LLMs and vector databases. Reduced inference latency by 40%. Led a team of 6, mentored juniors, and integrated AI into enterprise SaaS products for 100k+ users. Used MLflow and Prometheus for monitoring.

Flag of GERMANY

Munich, Germany

Oct, 2021 - Jul, 2024

•

2 years, 9 months

Senior Full-Stack Mobile Developer

Apr, 2014 - Sep, 2021

•

7 years, 5 months

MobileCraft GmbH

Apr, 2014 - Sep, 2021

•

7 years, 5 months

Developed and maintained cross-platform mobile applications using Flutter and React Native, with a Node.js/Express backend and PostgreSQL database. Architected RESTful APIs and implemented real-time features with WebSockets. Led a team of 5 developers, conducted code reviews, and introduced CI/CD pipelines using GitHub Actions. Optimized app performance, reducing load times by 30%. Collaborated closely with UX/UI designers and product managers to deliver features for 50k+ monthly active users.

Flag of GERMANY

Berlin, Germany

Apr, 2014 - Sep, 2021

•

7 years, 5 months

Education

Berufsbildende Schulen des Landkreises Osnabrück in Melle

2009 - 2013

•

4 years

Bachelor's degree

Flag of GERMANY

Germany

2009 - 2013

•

4 years

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