Rag jobs

Multi-tenant RAG SaaS. Python/FastAPI, , Supabase/pgvector. Full client isolation via Row Level Security. Per-tenant config set in admin panel: - AI mode: Cloud (Claude API), Local (Ollama/Mistral on client infra), or Hybrid (operational docs via cloud, sensitive docs flagged by category to local). Mode switch takes effect immediately, no redeploy. - Connectors: toggle OneDrive, Gmail, Outlook, Slack, WhatsApp per tenant. Each stores its own OAuth credentials encrypted. - Branding: logo initials, accent colour, company name, subdomain. - User roles per tenant: admin, analyst, viewer. - Pipeline confidence threshold per tenant (default 0.80). Six-phase pipeline: ingest, acquire (OCR/Whisper/pdf-parse), classify, extract entities, summarise, embed (pgvector). Routing logic: if mode=...

...as they install via and run fully offline. Deliverables 1. Complete, well-commented source code and 2. Setup guide and usage examples () 3. Recorded or live demo session showing ≥95 % extraction accuracy and correct answers on 20 validation questions drawn from the report If you have prior experience marrying PDF parsing with local LLMs or similar RAG workflows, I would love to see it. I’m ready to start as soon as we agree on an approach....

...for senior leadership (SteerCo level)**. What I Will Provide * Excel dependency tracker (fully populated) * Includes: * Dependency IDs and names * Upstream and downstream programs * Required dates * RAG status (Red / Amber / Green) * Impact levels * Cascade impact descriptions (cause → effect chains) * Impact category (Release, Program, Client, Financial) * Critical flag * Impacted milestone What You Need to Deliver 1. Executive Gantt Chart (PowerPoint) * Timeline-based Gantt view of all dependencies * Bars aligned to **Required Dates** * Color-coded by **RAG status** * Clearly labeled dependency names (NOT IDs only) 2. Cascade Impact Visualization (Critical Requirement) Each dependency must clearly show: * What it impacts downstream * How f...

We are looking for a Senior Developer with experience in Node.js, OpenAI API, and vector databases to finalize an AI chatbot. The chatbot is hosted on our VPS (Ubuntu), and the backend is already functional, connecting to MySQL for conversation history and Qdrant for RAG (Retrieval Augmented Generation) functionality. The main objective is to fix a critical bug and implement significant improvements within an estimated timeframe of 10 to 15 days. TASKS TO PERFORM: 1. Fix Error 400 (Token Limit): The file currently sends the entire MySQL history to the OpenAI API, causing the API to crash due to the token limit. A history management strategy is required, such as a sliding window (e.g., keeping the first message and the last 8 messages) or an active conversation summary. 2. Prompt

Freelance RAG Engineer (LLM Systems) – Evaluation & Optimization Project Overview We are building Yuktha, an AI-driven women’s metabolic health platform (starting with PCOS). Our system uses a Retrieval-Augmented Generation (RAG) pipeline to deliver personalized recommendations (diet, supplements, lifestyle, coaching) via mobile app and WhatsApp. A baseline RAG system is already developed. We are looking for an expert to audit, optimize, and scale the system for production-grade performance. --- Scope of Work 1. RAG System Audit - Review current architecture (retrieval, embeddings, prompting, orchestration) - Identify: - Hallucination points - Retrieval failures - Latency bottlenecks - Context leakage / irrelevant responses --- 2...

... I am looking to partner with freelancers (designers, marketers, consultants, no-code builders, etc.) who already work with clients but may not offer advanced AI or full-stack development services. You bring the client. I handle the execution. We share the revenue. What I Bring AI Development (Core Strength) LLM-powered applications (ChatGPT-like systems) Retrieval-Augmented Generation (RAG) systems AI agents and workflow automation Custom AI tools tailored to business needs Full-Stack Engineering Frontend: React (TypeScript) Backend: FastAPI / Node.js Databases: PostgreSQL and vector databases Scalable, production-ready deployment Automation and SaaS Systems End-to-end workflow automation AI-powered internal tools Subscription-based platforms Notification a...

...looking for an experienced AI developer to build a chatbot-based learning assistant. The system will: Answer subject-related questions accurately Generate practice questions based on patterns Provide structured learning plans Track basic user progress Technical Requirements: Strong experience with OpenAI API (or similar LLMs) Experience building chatbot / conversational AI systems Experience with RAG (Retrieval-Augmented Generation using documents/notes) Backend development (Python / Node.js) Database integration Nice to have: Experience with educational or productivity tools Full-stack development capability Please provide examples of previous work and relevant qualifications....

I need a professional-level PowerPoint one-page document that reflects an IT program's achievements and deliverables for Q1. Requirements: - Highlight project milestones and successful implementations for 15 projects under the program. Include completion percentages - Include results and current status with a bar chart - Emphasize next steps and potential risks/blockers with RAG status identifier Ideal Skills and Experience: - Expertise in creating corporate PowerPoint presentations - Strong understanding of IT program management - Ability to visualize data and program status effectively - Attention to detail and a professional design aesthetic

Title: Turn-Key RAG & AI Chatbot: 100GB+ Data Integration (Fixed Price) Description: We are seeking an expert AI/ML Architect to build a fully operational Retrieval-Augmented Generation (RAG) system. We have approximately 100GB+ of raw data (PDF, Excel, Word, PPT, Images) that must be transformed into a production-ready intelligence asset. The "Go/No-Go" Pilot Phase (Mandatory): This project begins with a 3–5 day Functional Prototype Phase. Requirement: Within 5 days, the consultant must provide a fully functional pilot demo using a representative subset of our data. Functionality: The prototype must demonstrate ingestion, vector search accuracy, and basic chatbot/report generation. Terms: Based on the pilot evaluation, we will decide whet...

Title: Build POC to Compare Normal RAG vs Graph RAG vs Tree RAG on Enterprise Knowledge Base Project Summary: I need an experienced AI/LLM engineer or small team to build a Proof of Concept that compares 3 retrieval approaches on the same real knowledge base documents: 1. Normal RAG (vector similarity / vector DB) 2. Graph RAG (entity + relationship + graph traversal) 3. Tree RAG (page / heading / section / hierarchy-based retrieval) The purpose of this POC is not only to make all 3 work, but to compare them fairly on the same documents and same question set, then recommend which approach works best for which question type. Main Goal: Build a working POC that can: * ingest the same source documents * create 3 separate indexes from the same doc...

...context on demand, and expose a clean API that downstream apps can call without worrying about the plumbing. What I already have: standalone LLM endpoints, a small library of task-specific agents, and an indexed knowledge base ready for RAG queries. What I need from you: the connective tissue. That means orchestrating calls between the models and agents, handling vector or hybrid search for the RAG layer, and implementing guardrails so the final responses stay on topic and safe. Deliverables • End-to-end workflow that links the LLM, agent manager, and RAG retriever • Clear, commented code or notebooks showing how each call is made • Minimal API (REST or FastAPI is fine) that external services can hit with a prompt and receive a consolidated answ...

...that improve how we deliver across the board. - Participate in client-facing meetings on an ad hoc basis, representing IzzyAgents with credibility and clarity. Required Skills and Experience - Strong, hands-on experience in applied AI development. - Proficiency with Claude Code is non-negotiable. - Solid knowledge of LLM APIs, including Anthropic and OpenAI. - Experience building and working with RAG pipelines and vector databases. - Familiarity with MCP (Model Context Protocol). - Experience with API and webhook integrations. - Confident in client-facing meetings, able to answer technical questions clearly and credibly, including with security and compliance teams. - Proactive, self-managing, and reliable in a remote, async-first environment. Working With Us IzzyAgents is a le...

...) This project proposes a hybrid RAG architecture that combines keyword-based retrieval with semantic search, adds a reward-and-punishment scheme to improve retrieval relevance, and uses ReComp-style context compression to handle long contexts more efficiently. [arxiv]() Background Retrieval-Augmented Generation is widely used to reduce LLM limitations such as knowledge cut-off, hallucinations, and lack of transparency, because it grounds generation in retrieved external evidence. Hybrid search is especially useful because keyword retrieval improves exact-match precision while semantic retrieval helps recover conceptually related content. [toloka](

...better) on PlantVillage images. Corn is the only crop for now, but feel free to enrich the training mix with compatible Kaggle sources if it boosts recall. The API receives a leaf photo, returns the detected disease name plus an evidence-based treatment guideline. 2. Chemical Compliance Assistant Using the dataset of “Allowed / Banned Agricultural Supplies” that I will share, build an LLM-powered RAG pipeline. The service must answer farmers’ free-text questions while refusing or correcting anything that contradicts the rules. Guardrails against hallucination are mandatory. 3. Yield Prediction Create a model—XGBoost is a strong candidate—that ingests live IoT sensor readings (JSON payloads: weather, soil moisture, temperature, etc.) together wi...

...Description: I have already completed Milestone 1 of my project (Islamic RAG system using Quran/Hadith data with strict output control). Now I need a developer to implement the Router Layer (Control System) before the existing /ask endpoint. This is a lightweight but critical component that will route user queries to the correct module. -------------------- Scope of Work: 1. Build Query Router When a user question comes in, classify it into one of the following modules: • islamic_rag • zakat_module • halal_scan • prayer_times • qibla_compass • general_chat -------------------- 2. Routing Logic Based on classification: • If islamic_rag→ apply query normalization→ send to existing RAG /ask endpoint • If zakat_module→ do ...

...*Requirements (MUST HAVE) Strong experience with LLMs (Gemini / OpenAI / Claude) Proven work in AI-based applications (chatbots, evaluation systems, etc.) Expertise in prompt engineering & structured outputs Experience with Node.js / TypeScript backend systems Understanding of AI limitations, hallucinations, and guardrails Nice to Have Experience building AI interview / assessment platforms Knowledge of RAG, embeddings, or evaluation frameworks Experience with real-time systems Deliverables Stable and consistent AI interview responses Structured and valid JSON outputs Improved evaluation accuracy Reduced latency and failures Clean, maintainable code improvements Project Type Short-term (initial fix: 1–2 weeks) Possibility of long-term collaboration To Apply, An...

...Multi-agent systems (planner, executor, verifier architectures) • AI workflows for risk adjustment, prior authorization, and provider engagement • RAG pipelines and tool-using LLM systems • Scalable AI infrastructure using cloud-native architectures Core Responsibilities • Design and implement agentic architectures • Build LLM-powered applications with high accuracy and reliability • Integrate healthcare data (FHIR, HL7, claims) • Develop evaluation and feedback loops for continuous improvement Required Qualifications • Strong Python and system design skills • Experience with LLMs, APIs, and distributed systems • Understanding of prompt engineering and RAG pipelines Preferred Qualifications • Experience with agent fram...

...AI system design across training, inference, monitoring, and lifecycle management Contribute to deployment reliability, reproducibility, CI/CD practices, and model monitoring Required Skills - 5+ years of experience in the AI/ML domain Strong Python skills Strong experience with AI/ML frameworks such as PyTorch, TensorFlow, or JAX Experience with LLM fine-tuning, prompt engineering, adapters, RAG, vector databases, and multimodal pipelines Strong grounding in classical ML, deep learning, NLP, CV, applied ML, and MLOps Experience designing end-to-end AI systems from training to inference to monitoring Experience with APIs, microservices, cloud platforms, and containers Strong problem-solving ability, communication, and ownership mindset Preferred - Experience building internal...

I need an experienced AI/ML consultant to architect and build a Retrieval-Augmented Generation (RAG) chatbot that streamlines internal workflows. The main goal is task automation: the bot should pull information from our proprietary data sources, reason over it with a large language model, and execute or trigger the relevant internal processes without human hand-holding. Core requirements • Retrieval + LLM pipeline: select, fine-tune or prompt-engineer the model, set up vector storage, and design the retrieval logic so answers always reflect our latest internal knowledge. • Secure integration with our internal systems (REST and a small GraphQL surface). Authentication must respect our existing SSO. • Clear separation between data ingestion, model inference, and...

I am building a premium, AI-powered advisory platform for senior leaders and board directors, built as an MVP-lite using an assembled, but coherent, stack rather than a full custom build. The core intelligence layer runs on Relevance AI (multi-agent, RAG-based advisory “panel” with persistent user memory), integrated with Stripe for payments, Brevo for CRM/email, Calendly for live advisory bookings, and Zapier to orchestrate data flows and triggers. The UX includes a structured, multi-stage conversation flow (decision framing, clarifying questions, assumptions panel, council synthesis, Founders personalised insights, reflection prompts, and a generated “Decision Intelligence Report” PDF), all of which must be reflected in how the front-end presents and labels...

...for a RAG (Retrieval-Augmented Generation) setup that uses our own content as its knowledge base, paired with a leading model such as GPT-4o or Claude. The tone must be lockable to our brand voice, and the assistant should be able to escalate seamlessly to a human when a query warrants personal attention. Key expectations ∙ End-to-end build: UX/UI, front-end, back-end ∙ Fast page loads and SEO-ready architecture ∙ Simple CMS so we can add resorts, articles, and itinerary content without touching code ∙ AI concierge built on a RAG pipeline using our resort content as the knowledge base ∙ Clear handoff documentation and a knowledge-transfer session on completion If you’ve built travel, hospitality, or directory-driven sites — and have demonstrable experience wi...

...AutoGen, or similar) Prompt engineering skills — writing effective system prompts, managing context windows, and building knowledge bases for LLMs Experience with HubSpot API (deals, contacts, tickets, pipelines, workflows) and API Experience building agents or bots that automate multi-step business processes (not just chatbots) Familiarity with vector databases (ChromaDB, Pinecone) and RAG architectures HTML/CSS for building dashboards and reports Experience working with a small team remotely across time zones Nice-to-Have: Python scripting (some of our automation uses Python) Experience with Pipedream or serverless deployment Familiarity with Anthropic's Claude API or OpenAI API Background in business process automation (not just coding — understanding why we...

...layer (wind in trees, distant wildlife) that can cross-fade into a contrasting sci-fi layer (low-frequency reactor hums, soft electronic drones) as the level progresses. • Character sounds – clean, varied footstep libraries (metal grates, dirt, concrete), a handful of short voice lines (think exertion grunts, short “ugh!” reactions, no narrative dialogue), and satisfying impact hits for melee and rag-doll collisions. • Interaction cues – clicks, beeps, gear slides and other one-shot SFX that respond to doors, levers and UI prompts. All assets must be royalty-free, delivered as 44.1 kHz/24-bit WAVs and logically named so I can drop them straight into MetaSounds or an FMOD bank. I’ll handle final mixing; what I need from you is creative ...

...The system must combine traditional Arabic NLP techniques/tools with LLM-based methods. Projects relying exclusively on LLMs without traditional NLP components will be penalized. Required Functionalities The assistant must support at least the following functionalities: - Conversational Question Answering: Answer user questions using a given knowledge base through retrieval-augmented generation (RAG). - Machine Translation: Translate text dynamically between Arabic and English. - Sentiment Analysis: Detect and report user sentiment during interactions. - Dialect Identification: Identify the Arabic dialect used by the user (e.g., MSA vs dialectal Arabic). - Text Summarization: Generate concise summaries for longer Arabic texts. Interface Requirements The assistant should be int...

This is a small sample task to test a developer before awarding a larger AI project. Scope: * Build a simple RAG-based chatbot * Use a small dataset (5–10 Quran verses or Hadith) * User asks a question (e.g., “What does Islam say about honesty?”) * System retrieves relevant verses * AI responds ONLY based on retrieved context * Response must include verse reference (Surah name + number) Important: * If no relevant data is found → respond “I don’t know” * No hallucination or generic answers Deliverable: * Working demo (simple UI or API is fine) Timeline: 2–3 days This is only a test project. Full project will be awarded after successful must be shared via GitHub with setup instructions.

...in real-time. Key Responsibilities: - Design and develop AI agents capable of autonomous decision-making and task execution. - Implement agent workflows using frameworks such as LangChain, LlamaIndex, or similar. - Integrate LLMs (e.g., GPT-4, Claude) for reasoning, generation, and tool usage. - Build multi-step reasoning pipelines (planning, memory, retrieval, execution). - Develop and manage RAG (Retrieval-Augmented Generation) systems. - Connect agents with external tools (APIs, databases, search engines). - Implement vector search systems (FAISS, Pinecone, ElasticSearch). - Design short-term and long-term memory systems for agents. Backend & System Development: - Develop scalable backend services using Python (FastAPI or Flask). - Build APIs to support agent interacti...

...structured and unstructured internal data ● Implement retrieval-based AI systems (RAG) using embeddings and vector search ● Integrate LLM APIs for query understanding and response generation ● Containerize and deploy services using Docker ● Develop simple internal web interfaces for non-technical users ● Implement business rules and safeguards to ensure reliable outputs ● Set up logging, monitoring, and feedback mechanisms ● Collaborate with business teams to translate workflows into technical systems Required Skills ● Strong backend development experience (Python – FastAPI/Django or Node.js) ● Experience with PostgreSQL or similar databases ● Understanding of APIs and system architecture ● Familiarity with RAG, embeddings, or vector search concepts ● Hands-on experi...

I’m building an AI-powered chatbot that follows the Retrieval-Augmented Generation pattern. The core service runs on Spring Boot, pulls context from a Pinecone vector index, streams prompts to OpenAI, and returns concise text-based answers. All application data and user sessions live in a MySQL database. What must be in place • Secure user authentication so each visitor has a private history. • Multilingual support—English to start, with the structure in place to add more languages through locale files and prompt templates. • Basic analytics and reporting: conversation counts, average latency, most-requested topics, and simple charts exposed via a protected REST endpoint or lightweight dashboard. Flow I expect 1. A user signs in. 2. Their query is vec...

Title: Build AI Halal Chatbot (RAG System with Quran & Hadith) – MVP Description: I am building an AI-powered Halal guidance platform called “Halaly AI”. The goal is to create a chatbot that answers user questions based strictly on authentic Islamic sources (Quran and Hadith) using a Retrieval-Augmented Generation (RAG) system. This is Phase 1 (MVP). Future phases will expand into halal products, travel, and finance. Scope of Work (MVP Only): AI Chatbot User can ask questions (e.g., “Is this halal?”, “What does Islam say about interest?”) AI must answer ONLY using provided Quran and Hadith or recognised historical context If no answer found, respond: “I don’t know” RAG Implementation Retrieve r...

...of Concept (PoC) for an AI/ML solution incorporating **Retrieval-Augmented Generation (RAG)**. The goal is to build a prototype that combines machine learning with contextual data retrieval to generate accurate, relevant, and dynamic responses. **Objectives:** * Develop an AI/ML prototype enhanced with RAG architecture * Enable the system to retrieve relevant information from a knowledge base and generate intelligent outputs * Validate the effectiveness, accuracy, and scalability of the solution * Demonstrate real-world use cases such as Q&A systems, document search, or intelligent assistants **Scope of Work:** * Understand project requirements and define system architecture * Design and implement a RAG pipeline (retriever + generator) * Prepare and preproce...

...pause and present a "Current Truth" summary for executive approval after the financial modeling phase before triggering high-cost document generation. Additionally, an Auditor Agent must be implemented to cross-reference legal narratives against financial tables to flag any hallucinations. Candidate Requirements: * Proven Experience: You have built complex, multi-agent AI systems (beyond simple RAG). * Domain Expertise: Familiarity with Real Estate Private Equity (REPE), LTV/LTC ratios, and land development workflows. * Technical Stack: Proficiency in Python, LLM Orchestration, API integration, and Document Engineering (Markdown/LaTeX to PDF). * Cost Efficiency: Deep understanding of Model Tiering and Prompt Caching to maintain low per-project operational costs. D...

...screening, and helping me figure out if someone is actually legit or just looks good on paper. Ideally, you’ve recruited for AI/ML roles before and you kind of know how to tell the difference between someone who’s built real systems vs someone who’s just done courses or copied projects. You don’t need to be super technical, but you should at least understand the basics — like what PyTorch is, what LLMs/RAG are, and what “production experience” actually means. Also, big plus if you know where to find good candidates beyond just LinkedIn Easy Apply — like GitHub, niche communities, or just smarter sourcing in general. If things go well, this can turn into a long-term thing. I’m not looking for a one-off hire. I’m flexi...

## RAG Expert Needed – Azure AI Foundry (Document Retrieval Fix + Explanation) **Project Type:** Consulting / Tutoring + Bug Fix **Platform:** Azure AI Foundry (Prompt Flow + Azure AI Search) **Duration:** Short-term (a few sessions) **Level Required:** Intermediate to Senior --- ### Project Overview I am building a RAG (Retrieval-Augmented Generation) application using Azure AI Foundry and Azure AI Search. The application is returning incorrect or irrelevant documents in response to user queries — and I need expert help to understand **why this is happening** and **how to fix it**. This is not just a fix request. I want someone who can **explain the root cause clearly**, walk me through what I am doing wrong, and guide me to implement the correct solution. I...

I need a fresh 30 × 30 cm graphic for an Amstel Bright rag that will be heat-pressed onto fabric. (one whole image)The artwork should marry the silhouette or iconography of the Amstel Bright bottle Place St. Maarten Carnival 55 years, with classic carnival energy—think festive shapes, confetti bursts, maybe a subtle steel-drum vibe—so both elements feel naturally integrated rather than layered on top of each other. Here’s what will help the project move smoothly: • Final artwork supplied as editable vector (AI or EPS) plus a print-ready 300 dpi PNG/PDF at true size. • Colors can be bright and tropical, muted, or strictly on-brand—show me your best proposal and we’ll lock the palette together before final export. • Design must h...

...evidence and RAG status. • People readiness – allocate role-based system access, verify system availability during the transition window and schedule all internal/external communications. • Contingency planning – document disaster-recovery steps, alternative service providers and any customer-facing fallback plans. Timing alignment Split the sheet so I can see activities: 1. “Pre-Migration” – everything that must be signed off before the migration event (this needs to dovetail with the master Schedule of Events). 2. “Post-Exit” – controls and clean-up items that continue after licence hand-back. Functional requirements • Excel (xlsx) only, no macros that require elevated security. • Drop-downs for sta...

I’m finalising a nutrition-focused mobile product and now need the server side that can truly “think” before it answers. The stack is Node.js with Express and MongoDB, and the core requirement is an LLM pipeline that relies on retrieval-augmented generation, never hallucination. Here is what I need you to engineer: • A RAG workflow that pulls only verified nutritional data from my Mongo collections and feeds it to the language model, with additive analysis treated as first-class information. Accurate ingredient analysis is the single most important metric for success, so the retrieval layer has to be rock solid and testable. • User context handling: every response must factor in stored health profiles— allergies, chronic conditions, dietary g...

Looking for B2B Client Acquisition Specialist (US Market) – AI/GenAI Services We are ZyHexo, an AI/GenAI engineering company specializing in RAG systems, AI copilots, and LLM observability solutions. We are looking for a client acquisition / lead generation specialist who can help us connect with US-based companies (AI startups, SaaS companies, and consulting firms) that need offshore AI development support. Responsibilities: Identify and research potential US clients (CTOs, founders, AI companies) Reach out via LinkedIn, cold email, and other channels Generate qualified leads and book meetings Maintain lead pipeline and follow-ups Requirements: Experience in B2B lead generation (preferably US market) Strong LinkedIn and cold email outreach skills Understanding of AI/tech ser...

...consecutive automated sessions without human intervention. 2. Responses draw only from the supplied documents; hallucinations or off-topic comments are grounds for revision. 3. Average response time under five seconds per question in a live test environment. 4. Clear deployment instructions so I can reinstall or migrate it on my own. If you have experience marrying LLMs (OpenAI, LangChain, RAG, etc.) with webinar or livestream platforms and can meet the criteria above, I’d love to see a brief outline of your approach and timeframe....

Homepage — Hero Messaging (Approved Copy) Primary Headline: Structure. Execute. Scale. Subheadline: SEAM is the operating company behind business systems and event execution. We help entrepreneurs ge...service_line in hidden fields. Install Google Tag Manager sitewide. Track event-based conversions (GA4 + Meta). Provide QA proof (GA4 DebugView + Meta Pixel Helper). Savor ordering: preferred external checkout (Square/Toast/etc.). Track outbound Order Now clicks with UTMs and an event (start_order). Ask SEAM™: implement as a WordPress plugin ([ask_seam] shortcode) plus a separate backend service for RAG + citations + agent orchestration. No NotebookLM dependencies. Compliance: exclude Trust services entirely. No ‘guaranteed’ language. Tax content is educa...

...Legal AI Assistant targeted to lawyers. The bot will analyze cases using OCR + AI, generate legal arguments from country law database, and handle evidence. Core Features (All Required): OCR Text Extraction: User uploads or take photo/PDF of handwritten/printed case documents (Arabic/French support). Use Tesseract or Google Vision API for accurate OCR → clean editable text. Smart Case Analysis (RAG): Analyze extracted text against country's laws database (I'll provide Penal Code + Civil laws as PDF/text). AI finds matching articles, legal gaps/loopholes, generates defense arguments with exact article numbers. Stick strictly to database - no external info. Evidence & Arguments Section: Separate upload for evidence photos/documents. OCR evidence text OR...

We’re hiring a strong full-stack developer for a full-time, long-term role. We are building an AI character platform and you’ll work on cutting-edge systems across: - AI image generation - AI text generation - Memory systems - RAG pipelines - Agentic workflows - Frontend and backend product development What You’ll Do - Maintain and improve our production + Laravel platform - Build features end-to-end (UI, APIs, data model changes) - Debug and resolve issues quickly with high reliability - Improve performance, quality, and system robustness - Collaborate on architecture and ship pragmatic solutions fast Non-Negotiables - Design quality is paramount: clean, polished, modern UX/UI execution - Bug-free delivery is paramount: high attention to detail and strong QA h...

...items cleared. Here is what the report surfaced as critical: • API Readiness Score • Rate Limiting configuration • Conversational Content Score • Semantic HTML Score & Alt-text coverage • Knowledge Graph entity mapping (Wikidata / DBpedia links) • E-E-A-T signal strength • Clarity & Evidence metrics (CCS) • Knowledge-graph integration hooks • Personalization data layer setup • RAG pipeline readiness • GDPR / CCPA compliance indicators & cookie consent • AI crawler allow-listing • Learning-loop implementation, regression detection, telemetry breadth, and error triage What I need from you: 1. Open the same report (I’ll share the PDF plus dashboard access) and verify each f...

We are bu...React Dashboard Refactor and improve the existing dashboard UI Build Agent Builder workflows and configuration screens Allow users to define tools and agent flows Implement real-time agent testing experience Manage agents by user account Improve stability, and code quality Requirements We are looking for a developer with: Strong Python experience, especially with AI/agent-based systems and RAG systems Hands-on experience with DSPy Solid React.js experience Good Laravel knowledge Experience designing and integrating REST APIs Experience with WebSockets and WebRTC Ability to write clean, production-ready, maintainable code Experience refactoring existing codebases and fixing architectural issues Project Type Existing product, not from scratch Refactor + ...

...touching the code. • Use Firebase or a small Node.js backend for authentication, storage and chat history. Design requirements A modern, clean UI that feels at home in an educational setting, with full Arabic / French localisation and right-to-left support. Deliverables 1. Complete source code for iOS and Android builds. 2. Setup scripts or docs that explain how to add new PDFs and refresh the RAG index. 3. A brief hand-off session to walk through deployment and basic maintenance. Performance expectations The install size should stay under 50 MB and typical answers must return within a few seconds on a mid-range device. If you have proven experience with cross-platform mobile development, AI chat integration and multilingual interfaces, let’s bring this tut...

...LLM/API usage Technical Requirements Must-Have Skills Strong experience in Python Experience with LLM integration (OpenAI, Anthropic, etc.) Knowledge of: Vector databases (FAISS, Pinecone, Weaviate, etc.) Embeddings & semantic search Experience with API integrations Familiarity with backend frameworks (FastAPI, Flask, etc.) Good-to-Have Experience with patent data or legal tech Knowledge of RAG (Retrieval-Augmented Generation) architectures Experience with LangChain / LlamaIndex or similar frameworks Understanding of patent search methodologies (novelty/FTO/validity) Deliverables Fully functional AI patent search backend system Modular architecture for: Query processing Search execution Result ranking Report generation API endpoints for frontend integration ...

...platform also produces a human-readable PDF tax summary and provides step-by-step instructions for manual submission to the IT Department's e-filing portal at eportal.incometax.gov.in. PHASE 2 An embedded AI-powered chatbot (TaxBot) provides real-time guidance on any wizard screen, grounded in the Income Tax Act 1961, CBDT circulars, and ITR-1 instructions through a Retrieval-Augmented Generation (RAG) pipeline. An optional human expert review service allows a support agent to access the user's return data — with the user's explicit in-platform consent — to provide personalised guidance. The platform is designed for three primary personas: Ramesh, a first-time salaried filer who needs hand-holding through every step; Savitri, a senior pensioner with l...

KI in GERMAN LANGUAGE I need a language model fine-tuned on dental learning content. This will be used to create an interactive quiz for adults. Key Requirements: - Fine-tune LLM on dental learning tool data - Generate content for adult interactive quiz Ideal Skills and Experience: - Experience with LLM fine-tuning - RAG-system, Python, PyTorch/TensorFlow
 - Ability to create engaging adult educational content

...• Flight Plans • Aircraft Schedules • Crew Schedules • MEL/CDL (Minimum Equipment List / Configuration Deviation List) data • Operational and route-based risk assessments • Weather and NOTAM data (preferred) • Additional airline operational datasets as required ⸻ AI Capabilities • Deployment of private LLMs (open-source or fine-tuned models preferred) • Retrieval-Augmented Generation (RAG) architecture for controlled knowledge access • Real-time and historical data querying • Explainable and auditable outputs for operational decision support • Ability to fine-tune or adapt models to airline-specific procedures ⸻ System Architecture • Private cloud (AWS/Azure/GCP VPC) or on-premise deployment • ...

I’m looking for someone who can track down and deliver the complete piano sheet music for “Rackety Rag” by J. Milton Delcamp. I want the original arrangement—no simplified or advanced edits—and I don’t need any added fingerings, annotations, or editorial markings. What matters to me is receiving a clean, legible PDF that represents the full score exactly as it was first published. Please locate a legitimate copy (public-domain archive, library scan, or licensed purchase) and ensure the file is free of watermarks or missing pages. Deliverable • One PDF of the full, original piano score for “Rackety Rag” by J. Milton Delcamp, complete and ready to print.

Project Overview I am looking for assistance evaluating and selecting a solution for semantic search across approximately 100,000 PDF documents. The system should support a retrieval-based architecture using embeddings and a vector database. Optionally, it may support a RAG-style workflow with an LLM, but the LLM must be optional and able to be disabled. When the LLM is disabled, the system should return relevant document excerpts only, avoiding generated answers. The main goal of the system is reliable document search, not a conversational chatbot. Requirements The proposed solution should: • Preferably use open-source or free-to-use tools with no mandatory licensing costs. • Have moderate computational requirements, suitable for running on a workstation or small server....