You will get Retrieve & Augment Knowledge (RAG) Systems for AI Applications | RAG
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Project details
Retrieve & Augment Knowledge (RAG) systems combine retrieval-based methods and generative AI models to provide accurate, context-aware responses in real time. RAG systems are designed to retrieve relevant knowledge from large datasets, augment it with generative models like LLMs, and deliver actionable insights or answers.
Key Objectives:
▪️Knowledge Retrieval: Efficiently search structured and unstructured data using advanced indexing and embeddings.
▪️Contextual Augmentation: Use generative AI models to process and summarize retrieved data.
▪️Scalable Architecture: Build a system capable of handling large datasets with low-latency responses.
▪️Custom Integrations: Integrate RAG with enterprise databases, APIs, and document repositories.
▪️Enhanced Accuracy: Implement feedback loops and fine-tuning to improve response relevance.
Project Scope:
▪️Development of a RAG pipeline with retrieval and generative modules.
▪️Integration with vector databases and knowledge stores.
▪️Implementation of query understanding, embedding generation, and context-aware augmentation.
▪️Optional: Multi-language support and domain-specific customization.
Key Objectives:
▪️Knowledge Retrieval: Efficiently search structured and unstructured data using advanced indexing and embeddings.
▪️Contextual Augmentation: Use generative AI models to process and summarize retrieved data.
▪️Scalable Architecture: Build a system capable of handling large datasets with low-latency responses.
▪️Custom Integrations: Integrate RAG with enterprise databases, APIs, and document repositories.
▪️Enhanced Accuracy: Implement feedback loops and fine-tuning to improve response relevance.
Project Scope:
▪️Development of a RAG pipeline with retrieval and generative modules.
▪️Integration with vector databases and knowledge stores.
▪️Implementation of query understanding, embedding generation, and context-aware augmentation.
▪️Optional: Multi-language support and domain-specific customization.
AI Algorithms
Autoencoder, Convolutional Neural Network, Feedforward Neural Network, Generative Adversarial Network, Large Language Model, Long Short-Term Memory Network, Multimodal Large Language Model, Recurrent Neural Network, Transformer Model, Variational AutoencoderAI Applications
AI Chatbot, AI Content Creation, AI Text-to-Speech, AI-Enhanced Classification, Conversational AI, Facial Recognition, Machine Translation, Natural Language Generation, Natural Language Understanding, Sentiment Analysis, Sequence Modeling, Text RecognitionAI Development Language
PythonAI Tools
Azure OpenAI, GitHub Copilot, Gradio, Hugging Face, Jasper AI, NVIDIA AI Platform, PyTorch, Streamlit, TensorFlowAI Models
BERT, BLOOM, ChatGPT, Dolly, GPT-3, GPT-4, LLaMA, OpenAI Codex, Stable Diffusion, WhisperWhat's included
| Service Tiers |
Starter
$1,999
|
Standard
$4,999
|
Advanced
$8,999
|
|---|---|---|---|
| Delivery Time | 21 days | 42 days | 70 days |
AI Model Integration | - | - | - |
Batch Normalization | - | - | - |
Database Integration | - | - | - |
Detailed Code Comments | - | - | - |
Image Upscaling | - | - | - |
MLOps | - | - | - |
Model Deployment | - | - | - |
Model Documentation | - | - | - |
Model Monitoring | - | - | - |
Model Testing & Optimization | - | - | - |
Model Tuning | - | - | - |
Natural Language Processing | - | - | - |
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | - | - | - |
Setup File | - | - | - |
Source Code | - | - | - |
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About Kamal
Full Stack Web Designer & Developer | AI/ML | UI/UX | SaaS | WordPress
100%
Job Success
Mohali, India - 12:49 am local time
What makes me different? I handle 𝗯𝗼𝘁𝗵 𝗱𝗲𝘀𝗶𝗴𝗻 𝗮𝗻𝗱 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁, which means no miscommunication between a designer and a dev, faster delivery, and a product that looks exactly as intended and works flawlessly under the hood.
𝗖𝗼𝗿𝗲 𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀:
🎨𝗨𝗜/𝗨𝗫 𝗗𝗲𝘀𝗶𝗴𝗻: Crafting clean, user-centered interfaces using Figma, including wireframes, interactive prototypes, and complete design systems. Proven experience on live commercial projects.
🖥️ 𝗖𝗠𝗦 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 & 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻: Implementing and customizing content management systems, including headless CMS solutions (Strapi, Sanity, Contentful) and traditional platforms (WordPress, Webflow).
⚡𝗙𝗿𝗼𝗻𝘁-𝗘𝗻𝗱 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁: Building pixel-perfect, fully responsive, and high-performance interfaces with React and Next.js, faithfully translated from design to production.
🔧 𝗕𝗮𝗰𝗸-𝗘𝗻𝗱 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁: Architecting robust, scalable server-side systems using Node.js (NestJS / Express) and Python, including REST APIs, third-party integrations, and database design.
🤖𝗕𝗼𝘁 & 𝗪𝗮𝗹𝗹𝗲𝘁 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁: Developing specialized technical solutions such as wallet systems for bot services, well-suited for fintech, SaaS, and automation-driven platforms.
📣 𝗠𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴-𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗲𝗱 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁: Delivering solutions with a clear understanding of how design and technology serve broader business objectives, including experience supporting digital marketing and business promotion initiatives.
I am a 𝟱-𝘀𝘁𝗮𝗿 𝗿𝗮𝘁𝗲𝗱 𝗳𝗿𝗲𝗲𝗹𝗮𝗻𝗰𝗲𝗿 with a consistent record of 𝗼𝗻-𝘁𝗶𝗺𝗲 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝘆, 𝘁𝗿𝗮𝗻𝘀𝗽𝗮𝗿𝗲𝗻𝘁 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗶𝗼𝗻, and 𝗹𝗼𝗻𝗴-𝘁𝗲𝗿𝗺 𝗰𝗹𝗶𝗲𝗻𝘁 𝗽𝗮𝗿𝘁𝗻𝗲𝗿𝘀𝗵𝗶𝗽𝘀 built on trust and results.
Whether the requirement is a product designed and built from the ground up, a complex 𝗳𝘂𝗹𝗹-𝘀𝘁𝗮𝗰𝗸 𝘄𝗲𝗯 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻, or the 𝗶𝗺𝗽𝗿𝗼𝘃𝗲𝗺𝗲𝗻𝘁 𝗼𝗳 𝗮𝗻 𝗲𝘅𝗶𝘀𝘁𝗶𝗻𝗴 𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺, I provide end-to-end ownership and accountability throughout the entire project lifecycle.
𝗟𝗲𝘁'𝘀 𝗯𝘂𝗶𝗹𝗱 𝘀𝗼𝗺𝗲𝘁𝗵𝗶𝗻𝗴 𝗴𝗿𝗲𝗮𝘁 𝘁𝗼𝗴𝗲𝘁𝗵𝗲𝗿, 𝗱𝗿𝗼𝗽 𝗺𝗲 𝗮 𝗺𝗲𝘀𝘀𝗮𝗴𝗲! 🚀
Steps for completing your project
After purchasing the project, send requirements so Kamal can start the project.
Delivery time starts when Kamal receives requirements from you.
Kamal works on your project following the steps below.
Revisions may occur after the delivery date.
Requirements gathering, dataset identification, and system design.
Setup vector databases, embeddings, and initial retrieval pipeline.