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I’m looking for a seasoned developer (or small team) to turn the idea of a cloud-native AI platform into a working product that automates tender intelligence for the Dominican Republic’s DGCP portal, with an initial focus on Technology-sector bids. What I need the platform to do • Automatically ingest DGCP tender notices, specifications, addenda, and Q&A. • Use NLP to analyze each document, extract key dates, requirements, evaluation criteria, and risk flags, then present the insights in a clean web-based dashboard (our only required output format). • Generate pre-filled compliance documentation that aligns our internal policies with each tender’s mandatory clauses. • Run lightweight process audits—flagging missing approvals, outda...

Busco un especialista en prompts que me diseñe un system prompt listo para copiar y pegar en casi cualquier modelo de lenguaje —excepto claude opus 4.6 thinking— capaz de “humanizar” el output y superar detectores de IA como GPT Zero. Lo necesito principalmente para la generación de ensayos, por lo que priorizo: • textos coherentes y sin contradicciones • fluidez natural de lectura • vocabulario suficientemente variado y sin repeticiones evidentes Entregables esperados: 1. Prompt completo con instrucciones claras (en español) para incorporarlo en distintos LLM. 2. Breve guía de uso: pasos para insertarlo, sugerencias de parámetros y ejemplos antes/después que demuestren la mejora frente a un detect...

I have an Arabic article about Arabic coffee (قهوة عربية) – its cultural significance, preparation rituals, and role in hospitality across the Gulf and Arab world. The article covers: The history of coffee in the Arab world How Arabic coffee is different from other coffees (lighter roast, cardamom, saffron) The dallah (coffee pot) and finjan (small cup) – their designs and meanings The ritual of serving – who gets served first, how to accept, how to refuse Coffee and dates – why they're always served together Regional differences (Saudi, Emirati, Omani, Jordanian) Modern coffee culture vs. traditional majlis coffee UNESCO recognition of Arabic coffee as intangible cultural heritage What I Need I need the full article translated into clear, natural Engl...

Executive Summary Signelle watches your data silently and delivers one short brief with practical, timely details. No dashboards. No noise. Just what changed, why it matters, and the impact, in plain language that leaders can act on.

Build an end-to-end AI application that can reliably solve JEE-style math problems, explain solutions step-by-step, and improve over time. The goal of this assignment is not just model usage, but to evaluate whether you can: design a RAG pipeline build a multi-agent system handle image, text, and audio inputs introduce human-in-the-loop (HITL) implement memory & self-learning package everything into a working application and deploy it You do not need to be a DevOps or full-stack expert, but you must be able to build, run, and deploy a simple app.

I need an AI-powered chatbot fully integrated with the WhatsApp Business API. It must converse fluently via text, understand incoming voice notes, and react appropriately to images or short video clips sent by users. I’m open on the underlying stack—Dialogflow, Microsoft Bot Framework, IBM Watson, or any other platform you believe best fits WhatsApp’s constraints—so long as latency stays low and the solution can scale as traffic grows. Core deliverables: • End-to-end WhatsApp Business API setup (webhook, number verification, cloud or on-prem hosting). • NLP pipeline that handles:  – Text intent recognition and response generation.  – Speech-to-text for voice messages, with the transcript feeding the same intent flow. &...

I’m building a voice-driven receptionist that greets visitors or callers, listens to their questions, and replies with a natural-sounding voice. The core flow is straightforward: • Speech-to-text: Accurate recognition of English only is required for now. • NLP: Classify the intent and pull the correct answer when a caller asks about our business hours or location. • Text-to-speech: Respond with friendly, human-like audio. • Fallback: whenever the system is unsure, it should politely ask for more details rather than handing the call off or giving a canned line. I need the full stack—STT, intent handling, response generation, and audio playback—wrapped in a module that I can drop into my existing website widget today and expand to a phone line ...

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’m building a voice-driven receptionist that greets visitors or callers, listens to their questions, and replies with a natural-sounding voice. The core flow is straightforward: • Speech-to-text: Accurate recognition of English only is required for now. • NLP: Classify the intent and pull the correct answer when a caller asks about our business hours or location. • Text-to-speech: Respond with friendly, human-like audio. • Fallback: whenever the system is unsure, it should politely ask for more details rather than handing the call off or giving a canned line. I need the full stack—STT, intent handling, response generation, and audio playback—wrapped in a module that I can drop into my existing website widget today and expand to a phone line ...

I want to roll out an AI receptionist whose single role is to speak with customers and give them clear, accurate information about our products and services. A caller (or site visitor) asks a question, the system turns that speech into text, pulls the correct answer from a knowledge base I will supply, and then replies in smooth, human-sounding audio—no appointment booking, no generic FAQ chatter, just concise product guidance. Here is the scope I have in mind: • Speech-to-text captures the question. • An NLP layer (LLM, Dialogflow, Rasa, or a framework you recommend) matches the query to the right answer. • Text-to-speech returns the response in natural audio, ideally with a custom voice so it feels branded. • The module plugs into either my website chat ...

I want an end-to-end Claude-powered agent that brings all of my buy-side research workflows under one roof. The agent must • Automatically pull PowerPoints, “Concall Transcripts”, annual reports from BSE or , and broker research (updates, downgrades, initiating-coverage notes) straight out of my one-year email archive • Parse each file, detect the company it belongs to, and save it in a dedicated Drive folder for that company—no mix-ups • Pass every saved document into NotebookLM and spin up a fresh notebook per company, ready for question-answering inside NotebookLM • Sit inside Microsoft Teams as a bot so I can type, for example, “Create notebook for HDFCBANK” or “What did the latest downgrade say about margins?” and get...

I’m looking for a Microsoft-stack AI engineer who can turn our customer-support scenarios into production-ready Copilot plugins driven by Azure OpenAI, Azure Functions, and an agent-orchestration layer such as Semantic Kernel. The natural-language work will run on Azure OpenAI (GPT-4 or GPT-3.5-Turbo). Business logic and data access belong in Azure Functions that you wire up through both Timer and Service Bus triggers; these functions will surface as OpenAI functions for the agent as well as REST endpoints for the plugin. The workflow itself needs to be orchestrated so the agent can decide which function to call and when—Semantic Kernel planners are preferred, but I’m open to an equivalent framework if you can show parity. Primary use case: live customer support and int...

Our Intercom inbox relies on FIN AI, yet too many chats still reach human agents. After digging into the analytics I’m convinced the root cause is the accuracy of the answers FIN serves, not the UI or core algorithm. I need an expert who can turn better training data into sharper, more dependable responses so customers self-serve more often. Here’s what I’m looking for you to do: • Audit recent conversation logs and the existing FIN knowledge base to pinpoint coverage gaps and misleading examples. • Curate or create high-quality, well-structured training data that directly addresses those gaps—think clarified FAQs, edge-case scenarios, and fresh intents drawn from real chats. • Prepare the dataset in the format Intercom accepts and guide (or h...

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...

Real-Time Face Swap System Requirements Specification 1. Project Overview Purpose: Development of real-time face replacement functionality aimed at protecting privacy and expanding expressive capabilities during streaming. Users: Exclusively for individual streamers. Streaming Environment: - Current: Mac mini (M4 chip, 16GB RAM) - Future: Upgradeable to 32GB/64GB as needed - OS: Mac preferred (portability priority), Windows compatibility considered if necessary - Streaming Software: OBS to be used 2. Non-Negotiable Requirements (Must Have) 2-1. Technical Requirements Face Replacement Specifications: - Replace only eyes and eyebrows - Use original parts for nose down (mouth/lips) - Reason: To prevent double lips when drinking liquids Safety: - Face processing must never drop out w...

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, ...

I want to launch a local delivery service here in Italy under my company name, Bistrosoftware. To do that I need a small web-based ordering system built around a chat interface that works equally well in text and voice. Here’s the flow I have in mind. A customer opens the widget on our site (or a standalone landing page), chooses either Italian or English, speaks or types an order, and the AI takes it from there. The bot must: • understand natural language questions about the menu (advanced NLP) • guide the customer through item selection, quantities, address and preferred delivery time (basic response handling) • present the PayPal checkout, confirm payment, then return an order number • keep the customer updated through the same chat thread as the ord...

I need an experienced AI/ML freelancer to take the lead on building a custom copilot that streamlines day-to-day clinical and administrative workflows for a healthcare platform. The immediate goal is to move from scattered manual steps to an intelligent assistant that can understand natural-language requests, pull data from our EHR, draft documentation, route approvals, and trigger follow-on actions inside existing tools. You will have full freedom to choose the right blend of large language models, retrieval-augmented generation, and automation frameworks, provided the result is HIPAA-compliant, auditable, and easy for my in-house dev team to maintain. LangChain, FastAPI, vector stores such as Pinecone or FAISS, and orchestration services like Airflow or Prefect are all on the table if t...

Infinity is the name I have reserved for an AI-driven web platform that functions first and foremost as an educational resource. I want a clean, scalable solution that lets anyone—from K-12 pupils to college, postgraduate or lifelong learners—store, organise, and retrieve knowledge in any field with the help of machine-learning features. Here is the vision in plain terms. Users create an account, upload or link their study material (PDFs, videos, lecture notes, articles or datasets), and the system instantly classifies, tags and indexes that content. A conversational AI layer (think ChatGPT-style) then allows them to ask questions, generate quick summaries, build flashcards, or create personalised study paths from their own resources plus open-access reference material pulled ...

My goal is to build an AI-driven pipeline that can read PDFs of medical subjects packed with both text and images, understand the material, and turn every chapter into student-friendly assessments. For each file the system should automatically deliver short-answer questions that capture key facts, long-answer prompts encouraging deeper explanations, and well-structured multiple-choice questions—complete with one correct option and plausible distractors. Because many of the PDFs include labelled diagrams, charts, or photographs, the engine must combine standard text extraction with reliable OCR so information buried in images feeds directly into at least one generated question. The tone and vocabulary need to suit secondary-school students, keeping accuracy on scientific terminology ...

I’m looking to have a fully-functional AI receptionist built that can pick up every inbound call, hold a natural conversation with the caller, and then route the call to the right person or department purely on the basis of what the caller actually says. The key outcomes I need are: • Advanced conversational AI – the system must go well beyond simple keyword spotting and understand context, intent, and follow-up questions so the interaction feels human. • Dynamic query-based routing – once the caller’s need is clear, the AI should transfer the call to the appropriate extension or external number automatically. • Clean hand-off – when the call is routed, the receiving party must get a short, accurate summary of the caller’s request...

I need a purpose-built CRM for the strata industry that leans heavily on AI to wipe out repetitive admin and give committees, owners and managers instant insight. The solution must weave in predictive analytics to flag maintenance and arrears before they surface, natural language processing so residents can lodge requests or search by-laws in plain English, and automated data entry that lifts information straight from invoices, minutes and inspection reports. The underlying platform is your call—web, mobile, desktop or a hybrid—so long as it comfortably scales to thousands of lots and high concurrent traffic without performance dips. Core functional areas I have in mind: • Centralised contact & lot database with role-based access • Ticketing thread that auto-cl...

1. Real-time Mesh Proximity Architecture Description: Establish a proximity-based mesh positioning network between the Master device (Coordinator) and Member devices (Nodes). Technical Approach: Utilize Bluetooth Low Energy (BLE) and Wi-Fi Direct to estimate relative distance. Requirements: The Master device must continuously receive signals from Nodes. If the RSSI (Received Signal Strength Indicator) of a Node drops below a predefined threshold (corresponding to a configured physical distance), the Master must trigger an alert notification. 2. Zero-touch Check-in Authentication Description: The system automatically scans and confirms the presence of Nodes within connection range. Technical Approach: The Master broadcasts a multicast packet via local network or Bluetooth. Nodes r...

I need an Arabic-language AI assistant that sits inside WhatsApp and takes over the entire patient-appointment workflow for my clinics. The focus is purely on scheduling—no medical diagnosis or FAQ automation—so the bot must understand, confirm, reschedule, and cancel appointments in natural Arabic without drifting into English. Core flow • Patient starts a WhatsApp chat. • Bot greets in formal Arabic, detects intent (new booking, follow-up, change, or cancel). • It checks available slots from my existing calendar (Google Calendar or a simple MySQL table—whichever you integrate fastest). • It offers the patient the next three open times, records the chosen slot, and sends an instant confirmation plus a reminder 24 h before the visit. • ...

I'm looking for a skilled Python developer to help build a web application integrated with Supabase. The project involves: - Database Management: Setting up and managing the database with Supabase. - API Integration: Connecting various APIs to enhance the app's functionality. - AI Implementation: Using Natural Language Processing to add intelligent features. Ideal skills and experience: - Proficiency in Python and experience with web development. - Strong knowledge of Supabase and database management. - Experience with API integration. - Expertise in Natural Language Processing. Please provide previous work examples and relevant experience in your bids.

I need an application that leverages AI to analyze market research survey data. The primary aim is to gauge public sentiment on social issues and government policy. Key Requirements: - Analyze survey responses - Identify key findings - Generate a report on ppt format with data visualization Ideal Skills and Experience: - Proficiency in AI and machine learning - Experience in data analysis, especially with survey data - Knowledge of sentiment analysis techniques - Ability to build user-friendly applications Looking for freelancers who can deliver accurate and actionable insights efficiently. Preferrably based in Singapore to facilitate face-to-face interactions.

We're starting a new freelance project on an AI-Based Call Transfer System for Telephone Exchange aimed at modernizing and automating call routing operations. This project will use artificial intelligence, speech recognition, and natural language processing to understand caller queries and automatically transfer calls to the correct department or officer without manual intervention. The system will reduce wait times, minimize human error, and improve overall communication efficiency. It will also include smart call prioritization, real-time monitoring, and performance analytics to enhance service quality and operational effectiveness.

Paid Voice Recording – Brazilian Portuguese (Native Speakers Only) We need 250 Females and 250 Males Speakers for long term recording project. We are expanding our current voice data project and are looking for additional native Brazilian Portuguese speakers to participate. You will record 370 short and simple sentences using our secure mobile recording app. The sentences are easy to read and require natural pronunciation only — no professional experience needed. Native speaker of Portuguese (Brazil) Android or iOS smartphone Quiet environment for recording Able to follow clear instructions Total lines: 370 Sentence type: Short and straightforward Estimated time: Around 30–45 minutes Recording completed inside our app 5 USD for completing all 370 sentences. If you ...

I need an NLP expert to help automate the analysis of text documents. Key Requirements: - Develop NLP models to analyze and extract insights from large volumes of text documents. - Improve data processing efficiency and accuracy. - Integrate solutions with existing systems. - Provide documentation and support for implementation. Ideal Skills: - Expertise in NLP and machine learning. - Experience with text analysis and data extraction. - Strong programming skills, preferably in Python. - Background in developing scalable AI solutions. Looking for innovative approaches to streamline data analysis and enhance productivity.

I want to turn my Instagram inbox into a fully-automated lead engine. The goal is a chatbot that sits on the Instagram Messaging API, detects new DMs in real time, and replies with natural, custom AI-generated answers—not canned templates. The first language it handles should be English, yet the model must gracefully switch to other languages when a visitor writes in them. Key objectives • Seamless integration with my existing Instagram Business account through Meta’s Graph/Messaging API. • GPT-class language model (OpenAI, Claude, or similar) that crafts context-aware replies while keeping brand tone. • Simple lead-capture routine: after a natural conversation the bot stores prospect data (we’ll finalise which fields) into a Google Sheet or CRM via ...

Saya tengah menyiapkan proyek kreatif yang memadukan ilustrasi digital dengan pemanfaatan Natural Language Processing. Fokus pertama saya adalah memperoleh satu gambar karakter full-color berkualitas tinggi. Di sisi lain, saya ingin mulai merintis model NLP dasar yang nantinya bisa diarahkan ke use-case terbaik—apakah chatbot, klasifikasi teks, atau terjemahan masih terbuka untuk diskusi. Ruang lingkup kerja: • Satu ilustrasi digital resolusi tinggi (layer terpisah, format PSD/PNG). • Dokumentasi singkat workflow gambar: software, brush, ukuran kanvas. • Notebook atau skrip Python yang membangun model NLP sederhana menggunakan library umum (TensorFlow, PyTorch, atau spaCy). • Panduan ringkas untuk melatih ulang model dengan dataset saya di kemudian hari. ...

Natafuta mtaalamu anayeweza kujenga kipengele cha AI kinachotambua lugha moja kwa moja kutoka kwenye maandishi. Lengo langu ni kupata mfumo mwepesi wa kuingiza kipande cha maandishi na kupokea majibu sahihi ya ni lugha gani imetumika. Niko wazi kwa mbinu zozote bora—iwe ni kutumia Python na maktaba kama spaCy, FastText, au modeli zilizofundishwa tayari za Transformer—mradi matokeo yawe sahihi na yapatikane kwa muda mfupi. Ikiwa una suluhisho la kutumia API zilizopo (mfano Google Cloud Translate au Amazon Comprehend) pia niko tayari kulizingatia, bora gharama zisiwe kubwa kupita kiasi. Ninahitaji: • Kanuni (source code) iliyoandikwa kwa usafi, ikifuatwa na maelezo mafupi ya jinsi ya kuiendesha. • Mfano wa faili ya kujaribu (demo script au notebook) inayoonesha utam...

Fokus saya adalah AI research, AI writing. Untuk mempercepat riset yang sedang berjalan, saya membutuhkan dukungan dalam menganalisis text data. Ruang lingkup pekerjaan: • Membersihkan dan menormalkan korpus teks (mis. menghapus stop-words, stemming, lemmatization). • Menyusun analisis statistik dasar—frekuensi kata, n-gram, distribusi panjang kalimat, hingga sentimen sederhana. • Menghasilkan visualisasi temuan kunci dalam format grafik atau dashboard interaktif. • Merangkum hasil ke dalam laporan singkat dengan rekomendasi langkah lanjutan yang relevan dengan AI writing. Teknologi yang biasa saya gunakan meliputi Python, Jupyter Notebook, pandas, spaCy, dan NLTK; silakan gunakan stack serupa atau jelaskan alternatif yang setara. Berikan kode yang t...

更多细节： Is this project for business or personal use? Personal What information should successful freelancers include in their application? Past work How soon do you need your project completed? Within a month

Fix RAG Service & Voice Interaction Issues in Python-Based Healthcare Application I need an experienced AI/ML developer to diagnose and resolve specific technical issues in a Python-based healthcare application that uses Retrieval-Augmented Generation (RAG) for content delivery and for AI voice agent integration. Specific Problems to Solve: 1. RAG System Issues: - Vector search returning irrelevant clinical content chunks - Embedding mismatches causing incorrect template retrieval - Context window optimization needed for accurate responses 2. Voice Interaction Bugs: - Speech interruption detection not triggering correctly - Silence timeout thresholds causing premature disconnections - Response retry logic failing after user interruptions 3. Content Validation: - Output filtering ...

My cloud-hosted Botpress chatbot already handles voice input, but two gaps keep it from feeling truly conversational. First, spoken replies are silent—text-to-speech is not yet wired in. Second, the current audio listener times out prematurely, forcing users to repeat themselves. Here’s what I need done: • Enable natural-sounding English TTS within Botpress. I’m open to Google Text-to-Speech, Amazon Polly, Microsoft Azure TTS, or another service you recommend, as long as latency stays low and integration fits Botpress’s hook/module system. • Diagnose and eliminate the audio-input timeout so the mic keeps listening for the full expected duration on every device and browser. • Deliver a short setup guide or commented code snippets so I can redeplo...

1. Project Objective To build a high-performance mobile application capable of seamless speech-to-speech and text translation without an internet connection. 2. Technical Stack AI Models: * Translation (NMT/LLM): Quantized (4-bit/8-bit) SLMs, specifically Gemma 2 2B, Llama 3.2 (1B/3B), or Phi-3.5 Mini. Speech-to-Text (STT): Offline Whisper models (Tiny or Base variants). Text-to-Speech (TTS): Integration of system libraries (Google TTS for Android / AVFoundation for iOS). Deployment Frameworks: * Inference Engines: Google MediaPipe LLM Inference API, TensorFlow Lite, or ONNX Runtime. Hardware Acceleration: Mandatory optimization for NPU and GPU (Apple A-series, Snapdragon, and Dimensity) to ensure energy efficiency. Development Platforms: Native development (Swift for iOS, Kotlin fo...

1. Project Objective To build a high-performance mobile application capable of seamless speech-to-speech and text translation without an internet connection. 2. Technical Stack AI Models: * Translation (NMT/LLM): Quantized (4-bit/8-bit) SLMs, specifically Gemma 2 2B, Llama 3.2 (1B/3B), or Phi-3.5 Mini. Speech-to-Text (STT): Offline Whisper models (Tiny or Base variants). Text-to-Speech (TTS): Integration of system libraries (Google TTS for Android / AVFoundation for iOS). Deployment Frameworks: * Inference Engines: Google MediaPipe LLM Inference API, TensorFlow Lite, or ONNX Runtime. Hardware Acceleration: Mandatory optimization for NPU and GPU (Apple A-series, Snapdragon, and Dimensity) to ensure energy efficiency. Development Platforms: Native development (Swift for iOS, Kotlin fo...

I already hold the patent designs for a pair of smart glasses; now I need them to come alive as a working prototype that I can place in front of investors. The hardware must fuse artificial-intelligence-driven voice recognition, an in-lens augmented-reality overlay, and continuous health-monitoring sensors, all packaged in a form factor true to my drawings. Core expectations • Firmware that supports hot-word voice commands and natural-language interaction processed on-device or via a lightweight edge AI stack. • A transparent AR display that renders contextual cues directly on the lens while maintaining normal vision. • Integration of basic biometric modules (heart-rate, step count, and SpO₂ ideal) with real-time data streaming. • A companion mobile app (iOS an...

I want to clone my own voice so that, during personal WhatsApp calls, everything I say is converted in real time and still sounds naturally like me. Accuracy takes priority over sheer speed or interface simplicity; the end result should keep my tone, inflections and emotions intact so callers cannot tell a difference. You will receive several high-quality recordings of my voice in different moods and volumes to train the model. The finished solution must run locally (Windows is ideal, macOS acceptable), route through a virtual audio device or similar method, and add no more than about one second of latency before the sound reaches WhatsApp. If you plan to leverage libraries such as RVC, So-Vits-SVC, PyTorch, TensorFlow, torchaudio or any comparable real-time voice conversion stack, please...

We’re looking for annotators to work on text-based tasks focused on validating accuracy, tone, and reasoning. The role involves editing and refining content, as well as creating structured reasoning chains that apply logical and linguistic consistency to complex customer–agent scenarios. Candidates should have a Bachelor’s degree, strong fluency in written English, and familiarity with composing or refining AI prompts. We’re looking for individuals with solid analytical and deductive thinking skills, an understanding of online shopping terminology, and strong attention to detail. The work will focus on three main areas: 1. Content Writing & Refinement Edit and refine AI-generated e-commerce content to ensure it sounds natural, authentic, and aligned wi...

Multilingual Voice Recording Project – Code-Switching Conversations Project Name: BV Project Type: Remote | Ongoing (Limited Slots per Locale) Project Overview Project BV is a multilingual speech data collection initiative designed to enhance Automatic Speech Recognition (ASR) systems for high-value multilingual call center scenarios, including financial services, healthcare, and telecommunications. The project focuses on collecting natural code-switching conversational audio, where speakers alternate between two languages within a single conversational turn. Scripts will be provided; however, natural delivery, fluency, and context-appropriate language switching are essential. Language Requirements Primary Language (Native level – one required): Arabic (arAE:UAE...