Transformare text în text AI Jobs

Enterprise RAG + Vector Search Implementation for AI-Powered Facility Management System" - "Production RAG System: Materialized Views + Vector Embeddings + LLM Integration" - "AI-Powered Knowledge Base: RAG Integration for Facility Management Platform" [Project Description (copy-paste ready):] I need an experienced AI/ML engineer to implement a production-grade Retrieval-Augmented Generation (RAG) system for our facility management platform. Scope: - Database optimization (materialized views, dimensioning) - Vector embeddings implementation (pgvector, Supabase) - Semantic search integration - Full-text search capabilities - RAG pipeline for TrackPlan + Armadillo data sources - LLM integration with Gemma 3 12B Deliverables: - Optimized database layer with materi...

I'm looking for an AI program to enhance my lifestyle productivity. The AI should help with: Task Scheduling and Reminders Goal Setting and Tracking Reminders and notifications should come through desktop notifications. Ideal Skills and Experience: - Experience in AI development, particularly in productivity applications - Familiarity with task management and goal tracking algorithms - Ability to integrate desktop notification systems. I would like the program to be capable of basic conversation and to be easily modified if needed

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 run a fast-growing digital-marketing and affiliate brand and now want to expand my offer with my own line of AI-powered products. The goal is to have fully white-label AI agents, together with the supporting automation strategies, that I can market under my name, keep 100 % ownership of, and scale for profit. Scope of the build Your primary mission is to design and deliver cloud-based or on-prem AI agents that can: • Generate complete ebooks on demand, including layout and ready-to-publish files • Produce kids’ paint books, puzzle books, IQ-challenge books and other children’s study materials • Assemble professional-exam prep books with up-to-date question banks and explanations • Power business-focused SaaS tools that solve everyday problems for...

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 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,...

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.