Hi, I’m Deepesh I design and deliver AI solutions that turn raw data into real business impact. Over the past few years, I’ve helped companies: • Build AI-powered search systems that can read thousands of PDFs and database fields using RAG + vector databases. • Deploy chatbots & NLP models to automate customer support and lead generation. • Create predictive models (credit scoring, fraud detection, sales forecasting) that improve decision-making. • Develop computer vision systems (e.g., textile defect detection) that cut manual inspection costs. My expertise includes: • Machine Learning & Predictive Analytics: Regression, Classification, Random Forest, XGBoost, SVM. • Deep Learning: ANN, CNN, RNN, LSTM. • Natural Language Processing (NLP): Text classification, intent detection, embeddings, chatbots. • Vector Search & RAG: Elasticsearch, Weaviate, FAISS, LangChain, OpenAI/HuggingFace embeddings. • Computer Vision: Image recognition, quality inspection, anomaly detection. Why clients work with me: • PG Diploma in AI & ML (upGrad + IIIT Bangalore). • Hands-on delivery of 8+ AI/ML projects (finance, manufacturing, research). • Experience with large datasets (millions of rows, 10k+ documents). • Blend of academic depth + practical industry results. If you need: • AI Search / RAG pipeline for PDFs or databases • Predictive analytics & forecasting models • NLP chatbots for support & automation • Computer vision for inspection & detection 👉 Let’s talk. I’ll design a clear tech plan and deliver a working PoC you can test before full rollout.

AI engineer. 30 jobs done on Upwork, $10K+ earned, 100% job success rate. What I mostly work on: → Agent systems. LangGraph, custom orchestration, MCP. Used for things like document analysis pipelines and internal company tools. → RAG. Pinecone or pgvector setups. Tuned for production, not just plug-and-play LangChain. → Full AI products. I've shipped paid marketplace apps and multi-agent backends. Real shipped products, not demos. Some recent work I'm proud of: Column Mate. A paid Monday marketplace app I built. Live on the Monday App Store (App ID 10601212). Pricing tiers from $0 to $300 a month. It has 4 features the leading competitor doesn't have, including the only AI Parse Updates feature on the whole marketplace. Auto Blog Automation. An n8n pipeline I built for a client. Cut their article production from about 4 hours per article to under 5 minutes. Publishes to 5 platforms automatically. Business Control Center. I migrated a flat-file JSON system to Postgres for a client. 9 migrations shipped. Dashboard reads under 100ms p95. My main stack: Python, Node.js, FastAPI, PostgreSQL, n8n, OpenAI, Claude, LangChain, LangGraph, MCP, Pinecone, Whisper, ElevenLabs. I'm bilingual, Arabic and English. I handle the full system: auth, billing, infra, all of it. Not just the AI parts. If you want a working system instead of a research notebook, send me what you're trying to build.

AI Development & Digital Transformation | LLMs, RAG, Agentic AI, Full-Stack | Expert-Vetted Top 1% I genuinely love helping businesses build kick-ass AI and custom software products and that obsession has earned Valere an Expert-Vetted Top 1% badge on Upwork, ranking us among the top 1% of software development talent on the platform. I'm Guy, CEO and founder of Valere. After 15+ years building, consulting, and launching consumer software products (including two acquisitions, one being a 15-million user app) I started Valere to help companies become AI-first through end-to-end engineering and transformation. We walk our clients through the whole process from AI planning and assessment, discovery, product design, technical solutioning, development, deployment, team adoption, AI upskilling/ AI coaching, and ongoing improvement. My ultimate goal is to help companies become AI-first by handling the full lifecycle and providing with tangible outcomes that we can all be proud of. There’s a lot of heart that goes into building impactful products. On paper, that looks like…300+ production deployments. $900M+ in measured client impact. 94% partner satisfaction. Clients include Fortune 500 companies, Johns Hopkins University, United Rentals, Mars, iHeartMedia, and CarShield. Client platforms we've built have helped raise $70M+ in venture and institutional funding. What my team builds: ✔ AI: Agentic systems, LLM applications, RAG pipelines, NLP, computer vision, ML, predictive analytics, generative AI, deep learning ✔ Web: React, Angular, Vue, Next.js ✔ Mobile: React Native, Flutter, Swift, Kotlin ✔ Back-end: Python, Node.js, .NET, PHP ✔ Cloud & DevOps: AWS, Azure, Google Cloud, Docker, Kubernetes ✔ Data: PostgreSQL, MongoDB, Snowflake, dbt ✔ Design: UX/UI, design systems, accessibility Who I work with: Venture-backed startups, PE-backed companies, mid-market businesses, and Fortune 500 enterprises across healthcare, finance, sports, fitness, education, and operations. Why clients choose us: ⭐️ AWS Advanced Tier & recognized AI/ML Partner ⭐️ Ranked #2 AI Services Provider on G2 a verified enterprise reviews ⭐️ Clutch Global Awards 2026 Top ML & AI Provider | Top 15 AI/ML worldwide ⭐️ Expert-Vetted Top 1% Agency on Upwork and featured in Upwork's 2023 Q2 Shareholder Report ⭐️ Selected for Upwork's Customer Advocacy Program, invited speaker at Upwork AI events ⭐️ The Manifest: Most Reviewed Developer 2024 ⭐️ Recognized Top 5 Trusted AI Agency by Tom Popomaronis Our AI transformation model: We transform companies into AI-first organizations through three tracks: Build (end-to-end AI and custom software development), Educate (AI workforce readiness via Valere Learning and General Upskilling through Evolve, our social platform), and Scale (proprietary products including Conducto, our agentic AI orchestration framework, and Dactic, our research automation platform). 225+ global professionals: AI Strategists, Data Scientists, Generative AI Developers, Agentic AI Engineers, UX Designers, Product Managers. U.S.-based oversight, 24/7 global coverage. Each client I work with gets decades of direct experience, through our engineers and through processes iterated on for YEARS across hiring, engineering, design, and QA. I'm OBSESSIVE about excellence. Anything less is unacceptable, which is why I only take on work we can execute at the highest level. If you have read this far, please note I appreciate you taking the time. I would love to learn about what you're building. Send me a message. Let’s chat!

Data scientist with remarkable experience in Python, statistics, machine learning, academic research and technical writing. I will happily discuss your project needs, so don't hesitate to invite me! Here are some of my professional accomplishments: • 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲𝗱 𝗣𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻𝗮𝗹: I have worked in various full-time roles and collaborated with numerous companies worldwide, thus acquiring significant experience and credibility. Feel free to check my previous work and project portfolio below. • 𝗔𝗰𝗮𝗱𝗲𝗺𝗶𝗰 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵𝗲𝗿: I have participated in EU-funded research projects, with published papers in Nature and other prestigious scientific journals. • 𝗣𝘂𝗯𝗹𝗶𝘀𝗵𝗲𝗱 𝗔𝘂𝘁𝗵𝗼𝗿: Simplifying Machine Learning with PyCaret became a bestseller and got cited in academic research. I am now working on a second book about time series forecasting. • 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗪𝗿𝗶𝘁𝗲𝗿: I have published numerous articles on topics like outlier detection, hypothesis testing, time series forecasting, large language models, and many others.

I am a research engineer focusing upon building and surpassing the latest and greatest in AI. My focus is on natural language processing (NLP) and multimodal (vision and text) AI, with a particular emphasis on large generative models. I have extensive experience working with a variety of different clients, from new startups backed by Y Combinator and AllenAI to large Fortune 500 companies. I have also provided consulting services, including to various venture capital firms and former Microsoft, AWS, and RTL Group executives hoping to build their own AI businesses. I am certified as a top 1% expert on Upwork and within the top 10% by Triplebyte. I also give talks across the industry - for example, I recently spoke on the Weaviate podcast about the current multimodal AI landscape. In terms of the models I am experienced with, I have worked with the vast majority of NLP and multimodal models as well as a significant amount of the speech and vision models available on Huggingface. I regularly build my custom model architectures to best fit client needs since while most models only really have one advancement they focus on, the clients I work with usually would benefit from the improvements from several different Huggingface models. However, I am also familiar with proprietary AI APIs, particularly that of OpenAI’s. I usually recommend those to clients who either will not see a lot of usage of their AI products for a while or those who have low maintenance costs being a top priority. Some of my favorite projects include: - Building a video summarizer taking as input a video or audio file and outputting a summary of its contents in either text or audio format. I used my own custom punctuation addition model, chunking and batching of speech inputs into 10 second increments to speed up transcription, TGlobal attention for the summarization system, and many other tricks. - Building a ChatGPT-style question answering chatbot built entirely with open-source models and tools - Creating a medical bill reimbursement system that took as input a picture of a medical bill, extracted the names of any relevant medical treatments, compared them using semantic search to reimbursable medical procedures in an insurer’s database, and automatically paid out money for all matches - Adding fine-tuning capabilities to MiniGPT-4 and other multimodal LLMs - Domain adapting CLIP on e-commerce data, reaching a 57% relative improvement in zero-shot classification after just 1 hour of training - Creating a custom training framework to train encoder-based language models using the replaced token detection (RTD) objective, including supporting weight sharing, custom generator sizes, training on multilingual datasets, adaptation of models not originally trained with RTD to be trainable using the task, etc. - Building a custom multimodal model architecture using linear attention - Reducing the size of the intent classification and NER models of an automotive company’s Alexa-style virtual assistant by 95-99% while improving accuracy - Creating the state-of-the-art ASL to English translation system back in 2021 (though I surmise this has since been dramatically improved upon since) Tech Stack: Model Development and Optimization - Huggingface, PyTorch, ONNX, Datasets, Pandas, Numpy, Scipy, SciKit-Learn, Sentence Transformers, PEFT, Accelerate, Loralib, TensorRT, Fairseq, LAVIS, TIMM, OpenNMT, TensorFlow, Jax, lots and lots of others Visualization - Matplotlib, tSNE, UMAP LLM Tools - OpenAI API (GPT-4, 3.5 turbo, Ada through davinci, etc.), Langchain, LLaMaIndex, Weaviate, Pinecone, Faiss, ScaNN Cloud - AWS (Sagemaker, EC2), GCP, Azure. I prefer to avoid cloud companies’ end to end AI services (e.g., Amazon Comprehend) since they tend to be inferior to open-source alternatives or things I can custom build, though I am open to using them if that is what you prefer!

I design and deploy production-grade AI systems: from data pipelines to scalable LLM applications. With 7+ years in ML/AI, I specialize in LLM systems, RAG architectures, and MLOps, helping teams move from prototype to reliable, scalable AI in production. My focus is not just building models but ensuring they perform under real-world constraints: latency, cost, hallucination control, and continuous improvement. What I build -End-to-end ML pipelines: ingestion, training, deployment, monitoring -RAG systems with proper evaluation harnesses (retrieval quality, regression catching) -LLM observability: prompt versioning, tracing, feedback loops -Scalable inference (real-time and batch) with GPU optimization -CI/CD for ML with MLflow, Airflow, automated retraining -AI agents with guardrails and reliable tool use Selected results -Fraud detection pipeline (real-time inference) → ~$890K in losses prevented -Forecasting system using ensemble models → 31% accuracy lift over baseline -Multiple LLM products running in production under client SLAs -$3M+ in measurable business impact across deployments (happy to walk through specifics on a call) Stack -Languages/frameworks: Python, FastAPI -LLMs: OpenAI, Anthropic, HuggingFace, LangChain, LlamaIndex -Vector DBs: Pinecone, Weaviate, ChromaDB, FAISS -Infra: AWS, Docker, Supabase, MLflow, Airflow How I work -Replies in 0–4 hours on business days -Production-grade code with tests and docs, not throwaway notebooks -Clear scope, direct communication, focused on business outcomes -Revenue, automation, speed-to-market — that's the scoreboard Let's turn your AI idea into a working product. Send an invite with your project details and I'll get back to you with a clear plan.

I am a highly experienced AI and Python developer specializing in Machine Learning. With hands-on expertise, I have successfully collaborated with over 767 international clients, delivering effective solutions across various platforms and industries. My projects include developing advanced chatbots, automated email systems, disease and clot prediction models, and real-time data dashboards tailored to client needs. Notable Achievements: AI-Trax Pulmonary Fibrosis: Enhanced prediction accuracy by 73%, surpassing competitors. Memorial University Mental Health Chatbot: Achieved 85% accuracy using open-source LLM and OpenAI API. Mumnoid Animal Classification: Attained 92% accuracy with complex CNN and GNN models. I offer services in machine learning projects, API integration, chatbot development, financial data analysis, and R programming. Eager to expand my expertise on Upwork and help elevate your projects. Let’s connect!

I build complete software products from scratch — requirements, architecture, backend, mobile, and deployment. My clients don't manage a dev team; they hand me a problem and get back a working system.

𝐀𝐈 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 | 𝐋𝐋𝐌 𝐀𝐠𝐞𝐧𝐭𝐬 | 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 & 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 I build AI-powered systems that automate real business workflows using LLMs, agents, and modern automation tools. With 7+ years of experience in AI/ML and data engineering, I now specialize in designing and deploying production-ready AI solutions using ChatGPT, LangChain, and workflow automation platforms. I focus on delivering systems that don’t just “look good” they save time, reduce manual work, and scale operations. 🔧 What I Can Help You Build ✔ AI Agents for business automation (multi-step workflows) ✔ ChatGPT / OpenAI integrations (custom apps, APIs, tools) ✔ RAG systems (document Q&A, knowledge bases) ✔ AI chatbots for customer support & internal tools ✔ Workflow automation (Zapier, Make, APIs) ✔ NLP systems (classification, routing, extraction) ✔ End-to-end AI pipelines (from idea → production) ⚙️ Tech Stack OpenAI (GPT-4 / ChatGPT API) LangChain / LLM Agents Python (FastAPI, backend systems) Zapier / Make (automation) Vector DBs (Pinecone, FAISS) REST APIs & integrations 💼 Recent Work Includes Built AI chatbot handling real customer interactions Developed LLM-based routing system for NLP classification Automated workflows using ChatGPT + Zapier Deployed LangChain-based document AI system Integrated LLMs into production APIs 🎯 What You Can Expect Clean, scalable, production-ready solutions Strong communication and fast turnaround Focus on business outcomes (not just code)

Hey, I’m Nirav, I did my Master’s from Columbia University and worked at UBS (core team) before starting Quantal AI giving me a strong foundation in both enterprise-grade systems and cutting-edge AI innovation. Today, I help startups and enterprises design, build, and scale AI Agents, LLM workflows, and automation systems that reduce costs, improve efficiency, and unlock new capabilities. My Core Skills: AI Agents (n8n, relevance ai, crew ai, make, Zapier, LangGraph, Langchain), LLMs, Generative AI, Chatbots, RAG, NLP with 7 years of Industry Experience. - Generative AI, LLMs, ChatGPT, Prompt Engineering,Machine Learning, NLP, Image Processing, Statistical Reports - Python and R, Data Modelling and Data Mining, Regressive, Predictive - Topic Modelling, Question-Answer Models, Computer Vision More than 7 years of Industry Experience with Python and Data Science: - Machine Learning : Pytorch, Keras, Tensorflow, Gensim, Scikit-learn, OpenAI, Langchain - Experience : 1. Projects: Generative AI, Sentiment Analysis, Semantic Clustering, ChatBots, E-Commerce Product Matching (Image and Text), Graph Data Mining, etc 2. Skills : Sequence Prediction, Text Classification, Text Generation, Summarization, Computer Vision and Image Processing 3. Architectures: LLMs, Transformers, Bidirectional LSTM, Graph Neural Networks, Attention Models, Reinforcement Learning EXPERTISE: AI Automation | AI App Development | AI Data Analytics | AI Model Training | AI Speech-to-Text | AI Text-to-Speech | AI Generated Code | AI Audio Generator | AI Bias Mitigation | AI Content Editing | AI Content Writing | AI Video Generator | AI Content Creation | AI Image Generation | AI Video Generation | AI Model Development | AI Model Integration | AI Writing Generator | AI Product Management | AI Mobile App Development | AI Enhanced Classification | AI Enhanced Medical Imaging