RAG n8n llm rag ak model

@toriquldev123

Hello Dear! I write to introduce myself. I'm Engineer Toriqul Islam. I was born and grew up in Bangladesh. I speak and write in English like native people. I am a B.S.C. Engineer of Computer Science & Engineering. I completed my graduation from Rajshahi University of Engineering & Technology ( RUET). I love to work on Web Design & Development project. Web Design & development: I am a full-stack web developer with more than 10 years of experience. My design Approach is Always Modern and simple, which attracts people towards it. I have built websites for a wide variety of industries. I have worked with a lot of companies and built astonishing websites. All Clients have good reviews about me. Client Satisfaction is my first Priority. Technologies We Use: Custom Websites Development Using ======>Full Stack Development. 1. HTML5 2. CSS3 3. Bootstrap4 4. jQuery 5. JavaScript 6. Angular JS 7. React JS 8. Node JS 9. WordPress 10. PHP 11. Ruby on Rails 12. MYSQL 13. Laravel 14. .Net 15. CodeIgniter 16. React Native 17. SQL / MySQL 18. Mobile app development 19. Python 20. MongoDB What you'll get? • Fully Responsive Website on All Devices • Reusable Components • Quick response • Clean, tested and documented code • Completely met deadlines and requirements • Clear communication You are cordially welcome to discuss your project. Thank You! Best Regards, Toriqul Islam

@webmasters486

Hi there, I’ve carefully reviewed the requirements for your GenAI project and I’m confident that my expertise in building NLP pipelines using Hugging Face and LangChain can meet your expectations. My experience includes working with large language models (LLMs) for Retrieval-Augmented Generation (RAG), as well as fine-tuning models with custom datasets to enhance text generation. I’ve successfully completed similar projects where I applied these techniques in Python to build robust, client-specific solutions. I would love the opportunity to discuss how I can leverage my skills to develop a tailored solution for your project. Feel free to take a look at my portfolio to get a sense of the work I’ve done: Portfolio: https://www.freelancer.com/u/webmasters486 Looking forward to hearing from you! Best regards, Muhammad Adil

@nutankumarftp

With over a decade of experience in PHP, I am well-versed in building robust and scalable digital solutions, making me the perfect candidate for your project. As a full-stack web and mobile app developer, I have successfully delivered 2000+ projects with 100% client satisfaction. This speaks to my ability to not just complete tasks successfully but also to ensure seamless integration with current systems, which is particularly crucial for your needs. Additionally, my background in designing user-centric applications and vast experience in handling APIs and database management (MySQL, MongoDB) equips me well to handle the complexity of developing an independent regulatory validation engine like RAG. My capacity to tailor solutions according to clients' unique goals will enable me to build a model that aligns precisely with your needs. Lastly, my portfolio showcases my proficiency in handling similar projects like yours. The creation of closed-domain AI video automation systems that require intense training as well as deep integrations with UI/UX is one such instance. I constantly prioritize client satisfaction, so you can rely on receiving a comprehensive and clear manual covering every step of the implementation process for this project. I aim not only to meet your expectations but exceed them. Considering all these factors, choosing me will be a decision you won't regret!

@khuzaima024

Hi, I have already done Rag agent check my profile. So, I will build your RAG engines and integrating them with n8n workflows Let Discuss further !!

@arslanshahid386

Hi there, It looks like you need a tailored RAG engine that operates strictly on uploaded documents post-final merge, without relying on external searches. My approach would involve developing this as a separate Docker container and ensuring it seamlessly integrates with your existing n8n-based AI video automation system. I’ll focus on connecting the data pipelines to maintain your workflow while delivering a structured JSON validation report that includes legal references. With 4+ years of experience in software architecture and AI development, I’ve worked on similar projects that required precise integration and validation functions. I’m confident that I can deliver a solution that meets your needs effectively. Could you clarify what specific legal references you would like included in the validation report? Best regards, Arslan Shahid

@hassansuhail

Hi there, I’m Hassan Suhail, a Python-first automation engineer with deep experience building closed-domain RAG systems connected to n8n via side-car APIs. I’ve delivered similar architectures where RAG runs as an isolated Docker service (FastAPI + Qdrant/PostgreSQL) validating final AI outputs without interfering in generation logic — exactly the pattern you described: post-merge validation only, structured JSON report output, and namespace-based vector isolation. For regulatory/validation RAG builds, my stack typically includes: • Python 3.11 + FastAPI side-car container • Qdrant (channel-specific namespaces) • Hybrid embedding + semantic chunking for large document ingestion • Strict closed-domain retrieval (no web search) • Structured JSON output (legal refs, confidence score, clause mapping) • Dockerized deployment with clean API contract for n8n HTTP node I’ve built RAG validation layers for compliance pipelines, document verification engines, and AI content control systems integrated with n8n, including full vector training pipelines and reproducible ingestion scripts. Estimated timeline: 7–10 days including containerization, namespace configuration, integration testing, and documentation (Google Sheets manual + walkthrough). Estimated fixed price: $450 USD for complete delivery + integration support. Happy to share architecture diagrams and previous RAG validation builds via DM. Cheers.

@adriank06

Hi there, I reviewed your architecture for the Regulatory Validation RAG. Keeping this as an independent validator via a Side-Car API that runs after the final merge (without interfering with the generation logic) is exactly how an enterprise-grade AI system should be structured. Portfolio & Related Experience: You asked for my related portfolio. As an R&D Lead specializing in Python and AI, I recently built and deployed a Financial AI Agent. Financial AI requires the exact same strictness as your regulatory engine: zero hallucinations, strict adherence to uploaded documents (closed-domain), and forced data formats. I have deep experience engineering LLMs to return strict, deterministic outputs rather than conversational text. My Approach to Your Requirements: Engine & Deployment: I will build the Side-Car API using FastAPI, fully Dockerized so it seamlessly plugs into your current environment. RAG & Namespaces: I will configure the pipeline (likely via LangChain/LlamaIndex) to target your pre-existing channel-specific namespaces in your vector database. Structured JSON Output: I will use strict output parsing (like Pydantic) to guarantee the API returns a JSON report containing the exact legal references for any OK/NG flags, analyzing both the final_merged_text and Vision tags. Mandatory Deliverables: Coming from an R&D background, rigorous documentation is my standard. You will receive the comprehensive Google Sheets manual (screenshots, prompts, configurations) and the walkthrough video. What vector database (e.g., Pinecone, Qdrant, Milvus) are you currently using for your channel-specific namespaces? I'd love to discuss the integration details. Best regards

@MohmedAbdelwahab

Hi there, I have extensive experience in building regulatory validation engines and deploying containerized applications with Docker, along with seamless API integrations using n8n workflows. I am confident in developing the RAG system as a standalone validation engine that processes final_merged_text and Vision tags to generate structured JSON reports with legal references. My expertise includes working with vector databases and closed-domain NLP models to ensure high accuracy. Additionally, I will provide a comprehensive Google Sheets manual with detailed steps, prompts, and configurations to support your team. Please share your budget and timeline preferences so I can tailor the proposal accordingly. Best Regards MohmedAbdelwahab

@jordanrafael7

Hello, I hope you are doing well. -> Previous Work: I’ve delivered Dockerized AI/ML back-ends for enterprise workflows, including RAG-inspired validation layers that run post-processing after data fusion. My recent setups involve separate containers with vector databases, side-car API communication (n8n), and closed-domain validation to ensure outputs stay anchored to uploaded documents. I’ve scaffolded microservices with clean architecture, secure data handling, and CI/CD pipelines, ensuring production-readiness for regulated environments. -> Development Plan: 1) Design a self-contained RAG engine container using a vector DB, accessible via a Side-Car API in the current namespace. 2) Implement a closed-domain validator that consumes final_merged_text and Vision tags, producing a structured JSON validation report with legal references. 3) Ensure RAG does not influence generation logic, only validates outputs. 4) Expose a Google Sheets-based manual in the requested format (prompts, steps, configs), and wire up data pipelines to downstream n8n flows and UI hooks. 5) Provide testing, documentation, and deployment scripts for Docker/K8s-friendly rollout. -> Schedule: - Kickoff and architecture review: 2 days - Container, DB, and Side-Car API setup: 4 days - Validation model implementation and tests: 4 days - Documentation, Google Sheets manual, and final QA: 3 days - Buffer: 1 day Tell me your portfolio related to this task, pricing, and timeline in clear terms suitable for a

@Intelliglance786

Hi, I am professional software engineer with skills including Software Architecture, Python, AI Development, LLM Integration, AI (Artificial Intelligence) HW/SW, XML, n8n, PHP, LLM Prompt Engineering and Retrieval-Augmented Generation (RAG). After reviewing the project requirements, I found the project perfectly match my experience and skills. Having previously worked on similar projects, I'm confident I can complete this project perfectly. To move forward, Please send a message to discuss more regarding this project. Looking forward to serve you

@Vsion2

Welcome to professional Python development services! Hi there, I'm Alema, a Python expert programmer who strives for clear code in atmospheric, numerical weather prediction, physics, and all other seminal fields. I'm ready to provide you with high-quality services. I have completed 350+ projects with a 100% Positive Rating. If you are looking for Quality work, look no further. Also, we are a team of professional workers, and we are always available 24/7 to help employers without limitations, and delivery is guaranteed on time. Your faithfully. Eng. Alema Akter

@syeds273

Hey , Thank you for sharing the job details. After going through the description, it’s clear you need someone confident with AI (Artificial Intelligence) HW/SW, LLM Integration, PHP, XML, AI Development, Software Architecture, n8n, Python, LLM Prompt Engineering and Retrieval-Augmented Generation (RAG) and can deliver clean, reliable results. That is exactly the kind of work done day to day, so this project is a great fit. Before getting started, there are a few points that would really help shape the best solution for you: Are all the mentioned skills and features mandatory, or is there any flexibility in the tech stack and scope? Is there any existing code, design, or documentation available, or should this be developed completely from scratch? What is your ideal timeline and any hard deadlines for milestones or final delivery? Why work with me? 1. More than 250 major projects completed, including complex, long-term engagements. 2. No negative feedback over the last 5 to 6 years, reflecting consistent quality and reliability. 3. 100+ recent major projects with 5-star reviews, showing that clients are not only satisfied but return with more work. Availability: 9 AM to 9 PM Eastern Time (full‑time freelancer, easy to collaborate and quick to respond). Portfolio: https://www.freelancer.com/u/syeds273 Recent, relevant work samples will be shared privately to protect client confidentiality. Please start the chat so we can finalize the project details, expectations, and

@automivex

Hello — I can build your closed-domain RAG validation engine exactly as required. I have 8+ years building AI automation, Docker microservices, and vector-based RAG systems integrated with n8n workflows. Relevant experience: • Dockerized RAG engines with isolated vector namespaces (Qdrant / Pinecone / Weaviate) • Closed-document compliance validation systems (no web search) • Side-car API microservices connected to n8n via webhook triggers • Structured JSON legal validation outputs with citation references • Vision + LLM multi-stage pipelines with post-generation verification layers For your system I will: ✔ Deploy RAG as a separate Docker container ✔ Connect via Side-Car API triggered after final_merged_text + Vision tags ✔ Implement strict closed-domain retrieval (uploaded docs only) ✔ Ensure zero influence on generation logic (validation only) ✔ Output structured JSON report with legal references ✔ Deliver Google Sheets manual (step-by-step screenshots, prompts, configs, video guide) Timeline: 1 - 2 days Price: $10 fixed You’ll get clean architecture, production-ready deployment, and seamless n8n integration. Ready to start immediately.

@mahads31

Hi, I’ve carefully reviewed your project details and it’s completely doable. This is exactly the type of web development work I handle regularly. I’m a skilled web developer with strong experience in XML, AI Development, PHP, Python, Software Architecture, LLM Integration, n8n, Retrieval-Augmented Generation (RAG), LLM Prompt Engineering and AI (Artificial Intelligence) HW/SW. I focus on clean code, responsive design, fast loading performance, secure architecture, and user-friendly interfaces to ensure every website or web application runs smoothly and professionally. You can also check similar projects in my portfolio on my profile. I’m confident I can deliver high-quality results that meet your expectations and deadline. Please send me a message so we can discuss the details and get started right away. Looking forward to working with you, Hope to hear from you soon