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In need for a skilled AI developer to create a an AI Agent for research, its core goal is to be an assistant system for me. This system will process and generate responses solely from documents that I upload. The use of DeepSeek or Chat GPT 12x7B or a comparable high-accuracy model is required. Key features should include: you have the freedom to use any of the following or suggest an alternative to establish my requirements : Option 1: Custom Chat UI + Retrieval Option 2: Pre-built RAG System + DeepSeek 12x7B Option 3: Quivr AI + DeepSeek 12x7B - Long-context processing - Retrieval-augmented generation (RAG) - Workspace-based document organization - Chain-of-thought reasoning - Citation generation The ideal system would be cost effective, scalable, and easy to maintain. I am open ...

I want to replace the manual US Calling sales calls my team is making with a fully automated, AI-driven outbound dialer. The system has to plug straight into our existing CRM so that every call is launched from, and written back to, a single customer record. Core workflow • The dialer should pull a lead from the CRM, place the call automatically, open a tailored script, and capture everything the prospect says through real-time speech recognition. • Natural language processing must understand intent and sentiment, while AI-driven responses keep the conversation moving until a meeting is booked or a hand-off to a human rep is required. • Once the call ends, the transcript, outcome, and next-step task should save to the same CRM record without anyone touching a keyboard...

I want to bring an AI layer into our existing Microsoft Teams environment so it can take over three day-to-day jobs for my group: project tracking, chat moderation, and task assignments. We already have well-defined workflows inside Teams, so the goal is to plug an intelligent assistant into what we are doing rather than rebuild anything from scratch. I am open to whichever engine suits the job—Zoom AI, Gemini, or any comparable platform—as long as it integrates cleanly with Teams and gives us clear, automatic reports on what is done and what still needs attention. Here is what I need from you: • Configure or build the AI integration inside MS Teams so it can read channels, pick up new tasks, assign or reassign owners, flag overdue items, and keep the conversation produc...

I want to feed every policy I hold into a ZohoOne workflow that automatically scans wording, limits, excesses and endorsements, then benchmarks them against both best-practice templates and current market data. The portfolio is broad—home insurance sits alongside property & allied perils, liabilities, medical, motor, fidelity guarantee, cash-in-transit, personal accident, marine cargo and hull, plant & equipment, inland transit, contractors all risk, political violence, cyber risks and SME PDBI—so the system has to recognise multiple classes and flag class-specific exclusions or sub-limits that could leave me exposed. The main outcome I’m after is a rock-solid identification of coverage gaps. Savings opportunities and risk-management enhancements are welcome, but...

I’m building a next-generation platform centred on Agentic Models—everything from single autonomous agents to full swarms and complex orchestrations that coordinate dozens of specialised LLMs at once. The immediate goal is to turn our R&D prototypes into production-ready systems, then keep scaling them until they can handle real-world, mission-critical workloads. Here’s what the role looks like day to day: • Architect and code large-scale agentic functions, swarms and orchestration layers that can reason, plan and act with minimal human guidance. • Integrate and benchmark state-of-the-art language models (OpenAI, Anthropic, Llama 2/3, etc.) alongside tools like LangChain, CrewAI, Semantic Kernel or your own preferred framework. • Optimise memory, ...

My small creative production studio needs a local, fully private AI stack that will sit on a 16 GB Mac Mini and behave like an operations assistant. I have already chosen the ai-stack-homelab project as the base; it ships with Dockerised n8n, Ollama (running Llama 3.2-class models), Open WebUI, PostgreSQL + pgvector, LiteLLM proxy and MCP integration. Your job is to install, configure and fine-tune that stack so it automates day-to-day admin without ever touching the public cloud. Immediate focus • Highest-priority workflow: detect inbound enquiries arriving via email, run them through the local LLM, then log each enquiry as a structured page inside my Notion space. No automatic replies for now—just clean, reliable capture so I can review and follow up manually. • Whil...

I run an e-commerce site and want a full-spectrum SEO and AEO upgrade. That means everything from tightening technical foundations (core web vitals, schema, crawl budget) to sharpening on-page elements such as keyword mapping, internal links, and AI-generated product copy, while also building an authoritative backlink profile. I’m especially interested in Answer Engine Optimization—rich snippets, voice search, and “zero-click” results—so structured data and content formatting for Google, Bing, and emerging AI assistants must be part of the plan. Please lean on AI tools where they truly add value; think GPT-powered content briefs, entity analysis, automated clustering, Screaming Frog for audits, Search Console data extraction, and SurferSEO or a similar platfo...

We run a precision outreach system targeting $5M to $10M business founders and CEOs. These are operators who have seen every pitch, ignore every template, and delete anything that smells like automation. One lazy message, one wrong word, one deviation from our voice standard damages brand equity with a prospect we may never get back. We need someone who takes that seriously and has the discipline to prove it. If you have executed AI-assisted LinkedIn outreach, know how to work inside a structured Claude prompt framework, understand the difference between executing copy and improvising it, and treat brand voice as non-negotiable, keep reading. If you are looking for a simple send-and-log role, this is not it. What the Work Actually Looks Like You will execute our UEC Apollo LinkedIn Out...

An App where people can find Maids, Nannys and Au-pairs near them in CapeTown South Africa Maids can also register and be vetted before they are put on the App ,they will need to upload their ID/passport 3 reference phone numbers (Relative-Work-friends) and a proof of address and expirience. Clients should put in their offer and Maids accept or can negotiate

I want an offline-running AI that studies each WhatsApp conversation, decides if a follow-up is actually necessary, chooses the best moment to send it, then drafts and fires off a friendly, contextual message—all without keyword tricks. The single most important benefit for me is saving the hours my team now spends chasing silent leads, so the system must be accurate enough that we can trust it to work on its own. How I picture the flow 1. A new or ongoing chat lands in our WhatsApp Business account. 2. Your model (hosted locally, not in the cloud) pulls the full thread, understands intent, sentiment, and stage of the sale from overall context. 3. If follow-up is warranted, it schedules the outreach intelligently—e.g., after an unanswered quote give it six business days,...

I need a ChatGPT-style assistant that can read every file my organisation generates—PDFs, Word docs, Excel sheets, HTML pages and anything else we store—then answer questions using that private knowledge base. The assistant must recognise the language of the query and reply in the same tongue; Hindi, Marathi, English and Telugu are the priority. The job covers the full pipeline: ingesting and parsing documents, building a semantic index or vector store, connecting it to a generative model and exposing everything through a simple chat interface. Whichever mix of OpenAI, open-source LLMs, embeddings or retrieval-augmented generation you choose is up to you, as long as the final experience feels as fluid as ChatGPT while keeping my data secure on our own servers. Please send a d...

I’ve built a hallucination-resistant LLM platform that already marries FAISS-based retrieval, answer cross-checking and modular knowledge-base support. The last piece that still feels brittle is the lightweight fine-tuning component. Today it performs well on the narrow domain data I trained on, yet I need it to generalize confidently across both technical subjects and varied industry-specific information without bloating compute costs. Here’s what I’m after: • Refresh the current LoRA/PEFT workflow or suggest an alternative that can stretch the model’s knowledge boundaries while keeping the footprint “lightweight.” • Curate or synthesize balanced tuning and evaluation sets that cover the two priority areas (deep technical content and sect...

Quiero poner en marcha un agente de voz / chat que automatice la gestión de citas y otras tareas con mis clientes. Ya tengo claras las piezas que deseo utilizar y necesito a alguien que pueda ensamblarlas con precisión: • Orquestación en (imprescindible). • Configuración del agente en Vapi. • Integraciones críticas: Google Calendar, WhatsApp Business API y base de datos Airtable o Supabase. • Uso de modelos vía API de OpenAI (GPT-4) y Anthropic, aplicando técnicas de prompting, funciones y RAG cuando convenga. Alcance del trabajo 1. Diseñar el flujo lógico completo del agente, cubriendo prompts, manejo de contexto y llamadas a funciones. 2. Conectar el agente con Google Calendar para gestionar r...

I’m ready to hand over the repetitive parts of my day—quoting jobs, sorting every incoming email, and filing project documents—to a single, smart system. The goal is an end-to-end AI-driven workflow that: • Generates job quotes automatically, including an accurate timeline, clear labour breakdown, materials list, and full price calculation. • Routes incoming mail into meaningful categories or labels so I can see what matters at a glance. • Saves and names related attachments or project files in the right folders without me touching them. I’m open on the tech stack—as long as the solution integrates smoothly with common tools (Gmail/Outlook, Google Drive or OneDrive, and a spreadsheet or lightweight database) and can expand later if workloa...

I need a single-page web application that lets a user upload a PDF, have an AI model (Claude or an equivalent LLM) extract the key entities and topics, then automatically query and LinkedIn with that data and display the freshest, most relevant results on screen. Core flow 1. User lands on the page, creates an account or signs in with a standard username–password form. 2. After authentication, they purchase a credit (pay-per-use). Stripe, Paddle, or a comparable gateway is fine as long as it supports one-off transactions and webhooks so I can reconcile usage. 3. With an active credit the user uploads a PDF. The AI parses it, identifies people, companies, keywords, and any other salient points you recommend. 4. The app fires off real-time searches to and LinkedIn, scrapes or calls ...

Dazzx is moving beyond simple template filtering toward a genuine Creative Layout Intelligence Engine. The platform’s canvas already renders static JSON designs; what is missing is the brain that, from three user inputs—uploaded assets, a short marketing prompt, and the chosen design size—can suggest the three strongest advertisement layouts out of a library of 10,000-plus templates. The assignment is to build that brain. The workflow I have in mind is: • Parse and understand the marketing prompt, extracting intent, tone, and any product cues. • Match those insights against our tagged template corpus, scoring each layout on visual hierarchy, probable asset fit, and relevance to the prompt. • Return the top three candidates as Fabric-compatible JSON, ...

We need raters to evaluate and rate the search results based on Factuality, Severity & Helpfulness of responses generated by GenAI LLM. You must be a native US based freelancer to participate for this project. You will need to have a rational & logical thinking ability having base knowledge of LLM/Gen AI, able to internet research. It is also important that you have a laptop or computer and a good internet speed. You will be required to work for around 5-6hrs/daily with a pay rate of $16/hr. If you can do more than that we are ready to assign you the work accordingly.