Do the following Stock Research Agent with SEC API and Weaviate RAG More information in the site
...put an AI tutor in every algebra student’s pocket. To make that happen, I need you to design and code a Retrieval-Augmented Generation pipeline that can understand a question, pull the most relevant snippets from my curated algebra textbooks, formula sheets, and problem sets, then explain the answer step-by-step with rock-solid reasoning. Here is what success looks like from my side: • A working RAG stack (embeddings → vector database → LLM) wired together with modern tooling such as LangChain, LlamaIndex, or an approach you can justify. FAISS, Pinecone, Weaviate, or similar are fine for the vector layer; OpenAI, Claude, Llama 2/3, or comparable models may drive generation. • Retrieval tuned for high recall and low latency—students should see a...
...banner underneath or built in to badge: Wash • Wax • Protect MASCOT (STRICT) Style must match the realism and structure of these brand references: - Hutton - Maston’s - Town & Country Requirements: - Semi-realistic (NOT cartoon) - Clean, structured proportions - Professional, confident expression - Clearly reads as a butler (formal attire) POSE / PROP Approved props: - Microfiber rag (preferred) - Spray bottle - Rag over shoulder Pose should feel: - Clean - Confident - Presentation-style (not exaggerated motion) WORDMARK OPTIONS Choose ONE layout: - RV stacked above BUTLER (preferred) - RV offset top-left - RV integrated into badge - RV BUTLER inline (same font, balanced) Rules: - BUTLER must be dominant - RV must still be clearly readable - The t...
...ecosistema de agentes inteligentes con arquitectura RAG para automatización de WhatsApp. La solución incluye: Motor de Agentes con RAG: Capacidad de respuesta inteligente utilizando bases de conocimiento personalizadas para cualquier sector comercial. Orquestador de Agentes: Sistema capaz de gestionar múltiples agentes especializados que trabajan en conjunto para resolver tareas complejas. Herramientas y Conectores Integrados: Conexión nativa con Shopify y WooCommerce para gestión de inventarios/ventas, y GitHub para flujos de trabajo técnicos. Escalabilidad Modular: Arquitectura diseñada para añadir nuevas "tools" y orquestadores según el crecimiento del negocio. Entregables: Fase 1: Despliegue...
Do the following Stock Research Agent with SEC API and Weaviate RAG More information in the site
...landing pages within GHL - Build CRM pipelines, automations, and workflows for clients - Integrate third-party tools (including AI chatbots and voice tools) into GHL environments - Troubleshoot GHL issues across sub-accounts Additional desirable skills - Closebot, Retell, n8n, AI Architecture & Implementation, ElevenLabs - Experience with vector databases (Pinecone, Weaviate, or similar) for building RAG pipelines and AI knowledge bases for clients who need custom LLM solutions with grounded data retrieval. HTML / WEB DEVELOPMENT** - Upload websites and landing pages (HTML/CSS) to hosting environments - Make minor front-end edits: copy changes, layout tweaks, image swaps, button styling - Comfortable working with existing codebases without breaking things - GHL page builde...
...Google Drive integration (read-only access) - Full Google Gemini API support - RAG (Retrieval-Augmented Generation) for intelligent document processing - Web interface for user-friendly querying - REST API for programmatic acces - Support for multiple file formats: PDF, Docs, Word, Text, CSV - Reusable template to create multiple independent knowledge bases Deliverables: - Fully functional connector application - Complete, well-documented source code - Configuration files and setup instructions - Web interface and API access - README and troubleshooting guide Requirements: - Strong experience with Python and API integrations - Familiarity with Google Drive API and OAuth2 - Ability to implement AI-powered querying and RAG systems - Clean, maintainable, production-ready co...
...Your focus will be to design, train, optimise and productionise state-of-the-art language models that reliably identify every relevant detail buried in those texts. The core task is named-entity recognition on complex legal prose. Models must capture the BIO boundaries and output rich entity labels while remaining performant at scale. I expect you to work comfortably with transformers, LLMs and RAG-style retrieval, refining them through techniques such as distillation, quantisation and pruning so inference stays fast and cost-effective. Entities to extract • Names and addresses • Legal terms and clauses • Dates and case numbers Alongside model work, you will own the MLOps path: packaging the model with Python and PyTorch, serving it through SageMaker (or...
...tree cultivation in Vietnam. The system requires 3 core REST APIs. All API JSON outputs must be in Vietnamese. The 3 Required APIs: Pest & Disease Detection (Computer Vision): Uses YOLOv8/EfficientNet to analyze leaf photos and identify specific coffee diseases (rust, pink disease, stem cracking) with >90% accuracy. Chemical Compliance Assistant (Vision + RAG): Takes an image of a chemical bottle, uses OCR to extract text, and uses a RAG pipeline (Langchain + Gemini/OpenAI) to check against our provided allowed/banned database. Must trigger a system action payload to "lock cultivation" if banned. Yield Prediction (Machine Learning): Uses XGBoost to process real-time IoT data (soil moisture, rainfall, etc.) and historical data to predict harvest yield. ...
AI. ZAKAT MODULE, QIBLA QAMBUS , HALAL SCANNER, PRAYER TIMES APP WITH MAP
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...
...multi-stage), AWS S3 y PostgreSQL. - Herramientas Pro: Tailwind CSS 4, Resilience4j y scripts auxiliares en Python. ¿Qué buscamos en ti? (Must-haves) - +7 años de experiencia en desarrollo de software, con al menos 2 años liderando equipos o tomando decisiones de arquitectura. - Docker: Builds multi-stage y despliegue en entornos cloud. - Expertise en IA: No solo conectas APIs; entiendes qué es el RAG, cómo evitar alucinaciones y cómo diseñar agentes con capacidad de razonamiento. - Experiencia en Proyectos SaaS: Entiendes qué significa construir para múltiples clientes desde una sola base de código. - Mentalidad de Producto: No solo tiras líneas de código; piensas en la experiencia ...
...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: 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 ...
...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...
Dev IA – Ecossistema Multi-Agentes – WhatsApp Contexto: Buscamos desenvolvedor para criar uma solução de atendimento automatizado via WhatsApp para uma agência de viagens. O foco total é privacidade de dados e especialização técnica. Requisitos Técnicos: Privacidade: Implementação de LLM Open-Source (Llama 3 ou superior) em nossa VPS/Servidor. Proibido o uso de APIs externas (OpenAI, etc). RAG (PDF): Inteligência para consultar bases documentais específicas de cada nicho. Arquitetura de Agentes: * Agente Orquestrador: Faz a triagem inicial. Agente de Sentimento/Qualidade: Monitora o estado psicológico do cliente, dispara gatilhos de retenção ou alerta humano se d...
...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...
