Web Design Studio | Brand Identity | Framer & AI Solutions
Web Design Studio | Brand Identity | Framer & AI Solutions
AI Automation Specialist | AI Agents, Voice Agents, n8n
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- Rating
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- Followers
AI Automation Specialist | AI Agents, Voice Agents, n8n
AI Engineer | RAG, AI Agents & LLM Applications
AthletiX Hub — Conversational AI E-Commerce Platform
Built a full-stack fitness supplement e-commerce platform with an integrated conversational AI shopping assistant.
AthletiX Hub combines a Flask backend, MySQL database, responsive web interface, and Dialogflow-powered chatbot to create a conversational shopping experience. Users can browse products and interact with the AI assistant using natural language to add or remove supplements, complete orders, calculate totals, generate order IDs, and track existing orders.
I developed the backend business logic, database integration, conversational workflow, session-based order management, webhook handling, and interactive frontend components.
The project demonstrates how conversational AI can be integrated directly into real e-commerce workflows rather than being limited to simple question-answering.:
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NLP Studio — Interactive Natural Language Processing Platform
Built an interactive NLP platform that brings multiple natural language processing capabilities into a single application. The system performs sentiment analysis, Named Entity Recognition (NER), Part-of-Speech (POS) tagging, and text processing on real-world text data.
I developed the complete application, including the NLP processing pipeline, model integration, backend APIs, and user interface. The project uses Python, spaCy, Scikit-learn, Pandas, and Flask to transform raw text into structured and actionable insights.
The project demonstrates my ability to take NLP models and techniques beyond experimentation and turn them into an interactive, usable AI application.
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AI-Powered Resume & Career Matching System:
Built an AI-powered career matching platform that analyzes candidate profiles and job requirements to identify relevant career opportunities.
The system applies Natural Language Processing and Machine Learning techniques to extract meaningful information from resumes and job descriptions, compare candidate skills with role requirements, identify skill gaps, and generate personalized career recommendations.
The project combines data preprocessing, feature engineering, NLP-based text analysis, similarity matching, and an interactive application layer to turn unstructured career data into actionable insights.
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Passionate Mobile & Web UI/UX Specialist
Passionate Mobile & Web UI/UX Specialist
20+ Founders trust me for AI Product, AI UX & Agentic UX. ⚡
- 10
- Followers
20+ Founders trust me for AI Product, AI UX & Agentic UX. ⚡
Hi there
I’m MD: Shahidul Islam. Working as a UI/UX Designe
- 12
- Followers
Hi there
I’m MD: Shahidul Islam. Working as a UI/UX Designe
Electric Car Mobile App
Hello,
Hope you're doing well. This is a, Electric Car Mobile App. Let me know what you are thinking about the design and don't forget to press the "L" button 😎
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UI/UX Designer | Fintech, EdTech, SaaS, B2B & B2C Designer
Tradecoin is a crypto trading web platform that helps users track the market and trade with confidence. This shot shows the Spot Trading screen in Buy mode, designed to let users analyze the market and place a buy order in one workspace.
The coin list on the left lets users switch pairs quickly, while the center holds a candlestick chart with timeframes, indicators, and volume. In Buy mode, the right panel turns green and shows Market, Limit, and Post Only orders, amount controls, and a live order book. Open orders, order history, trade history, and portfolio sit below the chart.
The Challenge
Trading screens can feel crowded and risky. Users switch between charts, order forms, and order books, and it’s easy to confuse a buy with a sell.
The goal was to create a focused trading experience with clear Buy and Sell states, so users always know what action they’re taking and can place orders with confidence.
Key Features
→ Green Buy mode with clear color feedback
→ Live ticker with top trading pairs
→ Coin list with search, filters & watchlist
→ Pair stats: price, 24h change, high, low & volume
→ Candlestick chart with timeframes & indicators
→ Market, Limit & Post Only order types
→ Amount slider with instant cost calculation
→ Iceberg order option
→ Max Buy & Total Cost details
→ Real-time order book & market trades
→ Open orders, history & portfolio tabs
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Tradecoin is a crypto trading web platform that helps users track the market and trade with confidence. This shot focuses on the Order Confirmation modal, which lets users review every detail of a limit sell order before they commit.
Placing a trade is a high-stakes moment. Users can make costly mistakes when order details are unclear or when they don’t fully understand how a limit order behaves.
The goal was to create a clear, trustworthy confirmation step that shows all order details, explains the risks, and helps users confirm with confidence.
I provide:
> UI/UX & Product Design
> Mobile App UI/UX Design
> Web & SaaS Design
> Landing Page & Website Design
> UX Research & User Flow
> Wireframing & Prototyping
> Design Systems & UI Components
> UX Audit & Usability Improvements:
> Responsive & Design QA
> MVP & Product Design
> Branding & Visual Design
> Pitch Deck Design
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Homiq is a mobile home services platform that makes everyday home maintenance easier and more convenient. The experience helps users quickly discover nearby services, explore trusted professionals, understand pricing, and book services without going through complicated steps.
The homepage focuses on fast service discovery, while the service detail experience provides important information such as ratings, pricing, availability, warranty, and service options before booking.
The Challenge
Finding a reliable home service often means too much searching, unclear pricing, and limited information before you book.
The goal was to create a simple, trustworthy, and easy-to-navigate experience that helps users move from discovering a service to booking it with confidence.
Key Features
→ Location-based service discovery
→ Quick service search
→ Popular & categorized services
→ Ratings & booking information
→ Clear service pricing
→ Instant service availability
→ Warranty & trust information
→ Flexible service scheduling
→ Add multiple services before booking
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AI Agents & Automation That Ship | Voice AI, LLMs, .NET
Not every automation needs an LLM. A B2B business was receiving purchase orders from retailers through SPS Commerce.
Someone on the team then checked stock by hand, retyped each order into Sage 50 as a sales order, and kicked off fulfillment.
We built a platform on ASP.NET (http://ASP.NET) Core and C# that handles it end to end.
→ Purchase orders come in through SPS Commerce automatically
→ Stock and order details are validated before anything is created
→ Sales orders land in Sage 50 without retyping
→ Anything odd is flagged as an exception instead of quietly slipping through Less manual work across the whole order lifecycle, cleaner data, and orders that keep moving without anyone copying fields between screens.
I build a lot of AI agents now. But the first question on every scoping call is still the same.
Does this need judgement, or does it just need wiring? Half the time it's wiring.
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An AI agent that can move money is only useful if it can't move it on its own.
Haia lets people manage their banks, crypto wallets and brokerages from one place, just by saying what they want done.
I built the AI orchestration layer. The interesting design choice wasn't the model. It was deciding where the model is not allowed to act.
→ The agent turns a request into a step by step plan
→ Each step is routed to the right banking API, wallet, chain or brokerage
→ Security and compliance checks run before anything executes
→ The user approves every move, and transactions are signed on their own device It's fully non-custodial.
Zero private keys ever exposed, to us or to the model.
If you're building agents that touch money, health records or anything you can't undo, design the approval step first. Then the AI.
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Your support team goes home at 6. Your customers don't. An online retailer we worked with had a simple problem.
Shoppers asked questions at 11pm, on weekends, on holidays.
The answers came the next morning, and by then a lot of them had bought somewhere else.
We built a 24/7 AI chat into their store. Not a FAQ bot that says "I didn't understand that" three times.
It handles the common questions on its own, recommends products inside the conversation, and drops every chat into their CRM with the full customer context.
When a person does step in, they aren't starting from zero. → 50% more conversions → 35% faster response time → 40% less support workload The part people underestimate is the CRM link.
A chat that sells but forgets who the customer is just moves the problem to your team. Support and sales turned out to be the same conversation.
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