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AI Data Annotation Specialist with experience delivering high-quality training data for Computer Vision, NLP, and LLM projects. I have successfully completed 30+ annotation projects across autonomous vehicles, warehouse safety, medical imaging, sports analytics, surgical tools, and object detection. My expertise includes: • Bounding Box, Polygon, Semantic & Instance Segmentation • Image & Video Annotation, Object Tracking, Keypoint Labeling • OCR & Text Annotation • NLP Data Annotation & Named Entity Recognition (NER) • LLM Training Data Preparation & Prompt/Response Evaluation • Sentiment Analysis & Text Classification • Quality Assurance & Accuracy Review Proficient in CVAT, Encord, Supervisely, SuperbAI, and other leading annotation platforms. I focus on accuracy, consistency, and scalable project delivery while maintaining clear communication and meeting deadlines. Whether you need a dedicated annotator or support for large-scale AI training datasets, I can help deliver reliable, high-quality results.

Some failures cost more than money. A healthcare platform that leaks patient data does not just pay a fine, it loses the trust of people who came to it vulnerable. A SaaS shipped without real security ships a liability. A WordPress project handed off without documentation creates dependency. I build so that does not happen. I am an AI harness engineer. I run frontier AI models, Claude and others, as an engineering harness to move from architecture to working, tested code fast, and I own every decision. I design the system, review every line, write the tests, and run the security scans before anything ships. You get the speed of AI with the judgment of an engineer who knows what a failure actually costs. Before code, I spent four years as a Physiotherapy Technologist in clinical care. I know what happens inside a clinic when a system fails a real patient, and that changes every architectural decision I make. Across 20+ production systems my work is verified by Prowler, Checkov, Trivy and SonarQube before delivery, not taken on trust. ───────────────────────────────────────── WHAT I BUILD ───────────────────────────────────────── AI, RAG and agent systems (the core of my work): LightRAG knowledge-graph pipelines, hybrid retrieval with Pinecone, BM25 and self-hosted cross-encoder reranking, multilingual embeddings, agentic and tool-use workflows, and multi-provider setups across Claude, Gemini and GPT-4 with a circuit breaker for uptime. HIPAA-safe chatbots with hallucination detection, PII scrubbing, grounding gates, zero-trust auth and full observability through Prometheus, Grafana and Loki. I also automate real business workflows end to end with n8n and LangChain. Healthcare and HIPAA platforms: telemedicine systems, dental clinic apps, patient portals and AI chatbots with HIPAA 2026, FHIR R4, GDPR and SOC 2 Type II enforced in the architecture and verified by automated scans. PHI encryption, audit logging, breach detection and RBAC are the foundation, not an afterthought. Cloud and DevOps: AWS, GCP and Azure together. Kubernetes on AKS and EKS, Terraform, GitHub Actions CI/CD, and a near zero-cost idle architecture at $2 per month instead of $300 on traditional infrastructure. Full stack SaaS: React 18/19, Next.js, Node.js, Python FastAPI, TypeScript, Supabase, PostgreSQL with RLS and pgcrypto, Stripe billing, multi-tenant architecture and Android apps via Capacitor. WordPress and Shopify: custom PHP plugins from scratch with OOP PHP 8.1 and PSR-4, headless WordPress and React via WPGraphQL and WooCommerce, Shopify Plus with Hydrogen, Shopify Functions in Rust and WASM, custom Remix apps on Cloudflare Workers, Contentful, Strapi, Elementor and ACF Pro. ADA and WCAG 2.1 AA remediation delivered for a real client in the USA. ───────────────────────────────────────── SELECTED PROJECTS ───────────────────────────────────────── MediConnect V3: tri-cloud telemedicine, 7 microservices, HIPAA/GDPR/FHIR R4, AI chatbot, 756 tests, $2/month idle. Yuktha Wellness (real client): production RAG health chatbot, 6 conditions, multilingual (Hindi, Tamil, Telugu, Bengali), Pinecone hybrid retrieval, code-enforced safety gates. RAG Production Stack: 23 containers, zero-trust 2FA, 6 compliance scanners, full observability. Fine Touch Marketing (real client): 17 n8n automation workflows, Claude-powered SEO and content, multi-site SMS follow-up. EquipCert AI: OSHA inspection SaaS, multi-AI, offline-first, GPS evidence, Stripe 3-tier billing. Chronos: headless WooCommerce and React, custom PHP plugin, WordPress 7.0 AI integration. RegenAI: Shopify Plus, Hydrogen, Rust/WASM Functions, custom Remix app, compliance-as-code CI. Groza Learning Center (real client, Los Angeles): ADA/GDPR remediation, 100+ errors fixed, zero theme modifications. EmailFinder, EDS Dental, HealthCode Analysis and more on my portfolio. ───────────────────────────────────────── HOW I WORK ───────────────────────────────────────── I do not disappear mid-project. I raise blockers early instead of going quiet, and you get accomfortable ones. Every delivery includes full source code ownership, complete documentation,and architecture clean enough to hand to any future engineer without confusion. Small WordPress fix or large HealthTech platform, the standard is the same. If I say I will deliver it, I deliver it. ───────────────────────────────────────── WHO I WORK WITH ───────────────────────────────────────── Healthcare platforms that cannot afford compliance failures. SaaS founders who need it built dding AI, RAG or agents to their product. Agencies managing complex deployments or needing real engineering depth. Developers with large backlogs who need a reliable build partner. ───────────────────────────────────────── ETHICAL BOUNDARIES ───────────────────────────────────────── I do not accept projects involving interest-based finance (Riba), conventional insurance, gambling, adult content, or any Haram activity.

𝗕𝗶𝗼𝗺𝗲𝗱𝗶𝗰𝗮𝗹 𝗼𝗻𝘁𝗼𝗹𝗼𝗴𝘆 & 𝐆𝐫𝐚𝐩𝐡-𝐑𝐀𝐆 𝐍𝐞𝐨𝟒𝐣 | 𝗖𝘆𝗽𝗵𝗲𝗿 𝗔𝗴𝗲𝗻𝘁 | 𝗣𝗶𝗽𝗲𝗰𝗮𝘁 | 𝐀𝐳𝐮𝐫𝐞 𝐒𝐞𝐚𝐫𝐜𝐡 | 𝗥𝗮𝗴 𝗙𝘂𝘀𝗶𝗼𝗻 | 𝗥𝗲-𝗿𝗮𝗻𝗸𝗶𝗻𝗴 | 𝗦𝗲𝗺𝗮𝗻𝘁𝗶𝗰 𝗖𝗮𝗰𝗵𝗶𝗻𝗴 | 𝐋𝐚𝐭𝐞 𝐂𝐡𝐮𝐧𝐤𝐢𝐧𝐠 | 𝐓𝐨𝐆 (𝐓𝐡𝐢𝐧𝐤-𝐎𝐧-𝐆𝐫𝐚𝐩𝐡) | 𝗥𝗔𝗚 𝗘𝘃𝗮𝗹 | 𝐌𝐢𝐜𝐫𝐨𝐬𝐨𝐟𝐭 𝐆𝐫𝐚𝐩𝐡 𝐀𝐏𝐈 I specialize in developing RAG and AI Agent systems with 15+ years of full-stack experience using LangChain, LangGraph, FastAPI, and vector databases (Qdrant, Pinecone, FAISS etc). For data ingestion, I build end-to-end pipelines supporting multi-format sources (PDF, DOCX, CSV, Excel, websites), structured cleaning with spaCy, Textacy & CleanText, web scraping via Playwright, BeautifulSoup & Jina Reader, Overlap Late Chunking for retrieval accuracy, and Microsoft Graph API integration for SharePoint/OneDrive across Microsoft 365.I also build real-time Voice AI agents using Pipecat with full STT → LLM → TTS streaming pipelines. My retrieval expertise covers Re-ranking (Cohere, FlashRank, Jina), dense/sparse/hybrid search, RAG Fusion, Semantic Caching, contextual compression, custom output parsers, LLM Token tracing, and RAGAS-based evaluation. I am a 𝐍𝐞𝐨𝟒𝐣 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐞𝐝 𝐏𝐫𝐨𝐟𝐞𝐬𝐬𝐢𝐨𝐧𝐚𝐥 specializing in Graph RAG, graph data modeling, Cypher queries, and domain ontology alignment. For graph ingestion, I have developed knowledge graph pipelines using GraphTransformers and NLP libraries for entity & relation extraction, aligned with domain-specific ontologies. For graph retrieval, I have implemented Graph Traversal, vector search, Think-On-Graph (ToG) reasoning, and Cypher Agents (generation, validation, correction, execution) leveraging LLMs for answers. Front End experience with TypeScript, Vue.js Composition API, Quasar Framework. I have a sharp eye for detail and quality and have experience of Software Reengineering. I am a self motivated individual who is both deadline focused and thorough in my approach to work. -------------------𝐏𝐫𝐨𝐯𝐞𝐧 𝐄𝐱𝐩𝐞𝐫𝐭𝐢𝐬𝐞 𝐢𝐧 𝐋𝐋𝐌 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭------------------- 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐑𝐀𝐆 & 𝐑𝐞𝐭𝐫𝐢𝐞𝐯𝐚𝐥 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 • Implemented RAG with multiple data formats (PDF, DOCX, CSV, Excel, TXT, websites etc.) • Enhanced retrieval techniques using RAG Fusion with multiple re-rankers (Cohere, FlashRank, Jina) • Applied optimization strategies like Prompt Caching, Semantic Caching with vector databases • Context-aware chunking is implemented by "Overlap Late Chunking" to improve retrieval accuracy • Conducted RAG evaluations using RAGAS for quality assessment and benchmarking • Built structured web scraping and cleaning pipelines using Playwright, BeautifulSoup, Jina Reader, Textacy, CleanText, spaCy etc. • Implemented dense, sparse, and hybrid search for advanced similarity search and optimal retrieval • Implemented LLM Token Tracing for monitoring LLM cost per user • Implemented custom output parsers for specialized formatting • Integrated Microsoft Graph API to fetch and process data from SharePoint and OneDrive across Microsoft 365 𝐊𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞 𝐆𝐫𝐚𝐩𝐡 & 𝐆𝐫𝐚𝐩𝐡𝐑𝐀𝐆 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 • Built Neo4j GraphRAG system with Graph Traverse and vector search capabilities • Created knowledge graphs aligned with domain-specific ontologies including bio-medical Ontology, using transformers, custom logic and detailed instruction-based prompts. • Developed Cypher Agents with LangGraph for Cypher generation, validation, correction, and execution • MS GraphRAG solutions with LanceDB and Parquet files, search and Indexing ,incremental indexing. • Successfully migrated MS GraphRAG Parquet files to Neo4j (KG) database systems 𝐋𝐋𝐌 𝐀𝐠𝐞𝐧𝐭𝐬 & 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐀𝐈 • Designed LangGraph Agent architectures for multi-step reasoning workflows • Built multi-agent systems with specialized roles • Applied advanced prompt engineering with few-shot learning and context window optimization • Developed real-time Voice AI agents using Pipecat for low-latency conversational interactions • Implemented streaming speech-to-text → LLM reasoning → text-to-speech pipelines 𝐅𝐮𝐥𝐥-𝐒𝐭𝐚𝐜𝐤 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 • Backend Development: Python, FastAPI for scalable services • Vector Database Integration: Qdrant, Faiss, LanceDB for efficient similarity search • Hybrid Application Development: Cross-platform solutions with Quasar Framework • Mobile Application Development: Expertise with Capacitor and Electron frameworks 𝐂𝐨𝐫𝐞 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬: - 𝐀𝐈/𝐋𝐋𝐌: Langchain, LangGraph, LlamaIndex, OpenAI, Claude - 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞𝐬: Neo4j, Qdrant, FAISS, LanceDB, Pinecone, Chroma - 𝐕𝐨𝐢𝐜𝐞 𝐀𝐈: Pipecat, Real-time Voice Agents, STT/TTS streaming pipelines - 𝐖𝐞𝐛 𝐂𝐫𝐚𝐰𝐥𝐢𝐧𝐠: FireCrawl, Jina, Puppeteer, Scrapy, Playwright, Beautiful Soup - 𝐃𝐨𝐜𝐮𝐦𝐞𝐧𝐭 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠: Llama Parse, Document Loaders, spaCy, Textacy

I'm a Senior Backend Developer and AI Integration Specialist with 10+ years of experience building scalable systems. I help startups and enterprises integrate AI capabilities into their products—from RAG-based chatbots to intelligent automation workflows. WHAT I BUILD: - AI-powered applications (RAG systems, chatbots, semantic search) - Production-ready backend systems (NestJS, Node.js, PostgreSQL) - SaaS platforms at scale (100K+ users, high concurrency) - AI integrations using OpenAI, Claude, and Langchain AI INTEGRATION EXPERTISE: - Retrieval-Augmented Generation (RAG) systems - Vector databases (Pinecone, Weaviate, ChromaDB) - LLM orchestration (Langchain, LlamaIndex) - Prompt engineering and cost optimization - Production AI deployment and monitoring CORE TECH STACK: Backend: NestJS, Node.js, TypeScript, Python Databases: PostgreSQL, MongoDB, Redis, Vector DBs AI/ML: OpenAI API, Claude API, Langchain Cloud: AWS, Docker, Kubernetes, CI/CD Tools: Cursor AI, Claude Code (AI-assisted development) RECENT EXPERIENCE: - Head of Engineering (Ai , Cloud and Infra) at Innospace Infotech (40-person engineering team) - Built Brritto MCQ platform (500K+ active users) - Created PocketSchool EdTech (500+ backend engineering students) - YouTube educator (35K subscribers, Bengali tech content) - Ai first watsapp CRM whtasmonk - Wedokan ai first ecommerce builder -Next Gen shop builder UNIQUE ADVANTAGE: I use AI-first development workflows (Cursor, Claude Code) to ship production features 10x faster. I don't just talk about AI integration—I live it. Let's build intelligent systems that deliver real business value.

I help startups, SaaS companies, and agencies turn designs, AI-generated prototypes, and existing products into production-ready frontend applications using Vue, Nuxt, React, HTML, CSS/SCSS, and modern AI-assisted development workflows. From pixel-perfect UI implementation and interactive experiences to frontend architecture, debugging, performance optimization, and code modernization, I build clean, maintainable, and production-ready software. What I can help you with • Design to Production Development (Figma, AI-generated UI & existing products) • Vue.js, Nuxt.js, React & Next.js Development • Responsive UI, HTML, CSS/SCSS & Complex Layouts • GSAP Animations & Interactive Experiences • Frontend Architecture, Debugging & Refactoring • Performance Optimization, Core Web Vitals & Accessibility (WCAG) • AI-assisted Development & Code Modernization Why clients work with me ✔ Production-ready frontend engineering—not just visually correct implementations ✔ Clean, scalable, and maintainable code that's easy to extend ✔ Reliable communication and AI-assisted workflows for faster delivery without compromising quality Recent Experience Over the past 8+ years, I've delivered responsive websites, SaaS products, landing pages, and frontend applications for clients worldwide. Recently, I've expanded into modern product development by building a hotel booking platform using Vue, Nuxt, Neon PostgreSQL, and AI-assisted workflows, along with AI-powered tools and Chrome extensions. If you're looking for a frontend engineer who can turn your design, AI-generated prototype, or existing application into a polished, production-ready product, let's discuss your project.

Most "AI voice agent" freelancers ship a demo that fails on the first real call, and most "AI SaaS MVP" builders ship a Lovable frontend with an OpenAI API taped to it. I ship the ones that don't break. Proof: two of my autonomous AI systems have run unattended on Facebook for months — Bengali Stoic and Calm Money Daily. I'm Faizul -- agentic AI engineer, Claude Code certified, IBM LLM Architecture certified, 8 years shipping software, 3 years focused on agentic systems that actually work outside a sandbox. You should hire me when: → Your VAPI or Retell voice agent works in the dashboard but breaks on real calls → You need multi-step voice logic (qualify → check inventory → book → sync CRM → follow up) that no-code tools can't handle → You want an AI SaaS MVP that actually functions, not just a Lovable frontend with an API call taped on → You need a custom MCP server, LangGraph agent, or OpenClaw deployment that survives production → You need an autonomous content or ops pipeline that keeps running — not another Zapier flow that breaks silently at 3am What I actually build: AI Voice Agents (VAPI + Retell + LangGraph) Production inbound receptionists, outbound lead reactivation, and multi-step call flows with real state, memory, CRM sync, and error handling. The parts most freelancers skip. Typical delivery: 2 to 3 weeks. Starting from $1,500. AI SaaS MVPs (Lovable + Cursor + custom agent backend) Full products in 2 to 4 weeks. Not a Lovable frontend with an OpenAI API call taped to it — a real agent backend underneath. Supabase auth with RLS, Stripe billing, Vercel deployment, clean architecture for future development. Starting from $2,500. Agentic AI Backends (LangGraph, CrewAI, MCP, Claude Code) Multi-agent systems, custom MCP servers connecting Claude to your internal tools, RAG pipelines on Supabase pgvector, and Claude Code workflows for non-technical teams. Includes evaluation, observability, and human-in-the-loop where you need it. Custom MCP servers from $800. Autonomous Content and Ops Pipelines (my own proof) Six-stage autonomous agents built on Gemini, Pillow, APScheduler, and the Facebook Graph API. Bengali Stoic (Bangla Stoic philosophy content) and Calm Money Daily (US personal finance) have both run unattended for months, publishing daily without me touching them. Same architecture works for your outbound sequences, weekly reports, or internal ops. Verticals I work with: → Home services (HVAC, plumbing, roofing) — inbound call capture, after-hours booking → Med spas, dental practices, clinics — appointment booking, patient intake → Real estate teams — lead qualification, follow-up sequences → B2B SaaS founders — MVP builds, agent features inside existing products → Marketing and content agencies — white-label agent builds → E-commerce brands — automated customer support, order lookup, returns How I'm different: Most competitors keyword-stack without shipping proof. I have live production systems you can look at today. Most rush to code before scoping. I write the architecture doc first, so you know what's shipping before you pay a milestone. Most build for the demo call. I build for month six, when your client volume tripled and the system still has to work. Tech stack: Agents: LangGraph, CrewAI, MCP, OpenAI Agents SDK, OpenClaw, LangChain LLMs: Claude Sonnet and Opus, GPT-4o, Gemini Voice AI: VAPI, Retell AI, Twilio, ElevenLabs, Deepgram Frontend / MVP: Lovable, Cursor, React, Next.js, Tailwind Backend: Python, FastAPI, Node.js, Supabase (pgvector, RLS, edge functions), PostgreSQL Automation: n8n, Make, Claude Code, custom MCP servers Infra: Hetzner VPS, Docker, Vercel Certifications: → Claude Code Certified (Anthropic) → IBM LLM Architecture Certified How we'll work: Free 20-minute scoping call -- I map your actual process, not my toolkit Written architecture doc before any code, so you approve scope and timeline Milestone-based delivery -- no lump sums, no surprises mid-project Full documentation and clean handoff so your team owns what I ship 30 days of post-launch support included What I don't do: → Pure strategy work or AI consulting retainers without shipping code → Open-ended "AI can it do X" discovery calls with no scope → Sandbox demos that aren't intended to reach production → Cheap Fiverr-style $50 gigs — the math doesn't work How to hire me: Send me a message with these four things and I'll reply within 24 hours with an honest assessment — including if I think I'm not the right fit: What you're building, or what's currently broken Your current stack (or "starting fresh") Your timeline and budget range What "done" looks like for you I ship systems that keep working after the demo call. That's the whole offer.