Featuring Labeled Customer Emails and Support Responses

Network Diagram Tags

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Discover the new, expanded version of this dataset with 20,000 ticket entries! Perfect for training models to classify and prioritize support tickets.

Definetly check out my other Dataset:
Tickets from Github Issues

It includes priorities, queues, types, tags, and business types. This preview offers a detailed structure with classifications by department, type, priority, language, subject, full email text, and agent answers.

Features / Attributes

Queue

Specifies the department to which the email ticket is categorized. This helps in routing the ticket to the appropriate support team for resolution. - 💻 Technical Support: Technical issues and support requests. - 🈂️ Customer Service: Customer inquiries and service requests. - 💰 Billing and Payments: Billing issues and payment processing. - 🖥️ Product Support: Support for product-related issues. - 🌐 IT Support: Internal IT support and infrastructure issues. - 🔄 Returns and Exchanges: Product returns and exchanges. - 📞 Sales and Pre-Sales: Sales inquiries and pre-sales questions. - 🧑‍💻 Human Resources: Employee inquiries and HR-related issues. - ❌ Service Outages and Maintenance: Service interruptions and maintenance. - 📮 General Inquiry: General inquiries and information requests.

Priority

Indicates the urgency and importance of the issue. Helps in managing the workflow by prioritizing tickets that need immediate attention. - 🟢 1 (Low): Non-urgent issues that do not require immediate attention. Examples: general inquiries, minor inconveniences, routine updates, and feature requests. - 🟠 2 (Medium): Moderately urgent issues that need timely resolution but are not critical. Examples: performance issues, intermittent errors, and detailed user questions. - 🔴 3 (Critical): Urgent issues that require immediate attention and quick resolution. Examples: system ...

📬 Bilingual Ticket Classification Dataset

This dataset is a balanced and augmented version of the Customer Support Tickets dataset, designed for multilingual text classification tasks. It has been balanced across three key features, language, queue, and type, ensuring that each combination contains approximately 100 samples. Balancing was achieved through back-translation and data augmentation techniques applied to the original dataset.

  📊 Dataset Overview

Split:… See the full description on the dataset page: https://huggingface.co/datasets/ale-dp/bilingual-ticket-classification.

kshitizgajurel/Multilingual-Nepali-Customer-Care-Services-Dataset dataset hosted on Hugging Face and contributed by the HF Datasets community

We provide a wide range of off-the-shelf multilingual audio datasets, featuring real-world call center dialogues and general conversational recordings from regions across Africa, Central America, South America, and Asia.

Our datasets include multiple languages, local dialects, and authentic conversational flows — designed for AI training, contact center automation, and conversational AI development. All samples are human-validated and come with complete metadata.

Each Dataset Includes:

Unique Participant ID

Gender (Male/Female)

Country & City of Origin

Speaker Age (18-60 years)

Language (English + Multiple Local Languages)

Audio Length: ~30 minutes per participant

Validation Status: 100% Human-Checked

Why Work With Us: ✅ Large library of ready-to-use multilingual datasets ✅ Authentic call center, customer service, and natural conversation recordings ✅ Global coverage with diverse speaker demographics ✅ Custom data collection service — we can source or record datasets tailored to your language, region, or domain needs

Best For:

Speech Recognition & Multilingual NLP

Voicebots & Contact Center AI Solutions

Dialect & Accent Recognition Training

Conversational AI & Multilingual Assistants

Customer Support & Quality Analytics

Whether you need off-the-shelf datasets or unique, project-specific collections — we’ve got you covered.

http://filemarket.ai

💬 az_customer_support-v1.0

Description:6,000 multilingual (Azerbaijani–English) instruction–response examples for common customer support scenarios.Covers diverse intents such as checking invoice status, canceling or modifying orders, tracking shipments, and more.Each entry includes the user's query (in English and Azerbaijani), the categorized intent, and a well-structured support response tailored to the request. Use Cases:

Instruction-tuning for multilingual customer service… See the full description on the dataset page: https://huggingface.co/datasets/az-llm/az_customer_support-v1.0.

Dataset summary

Multilingual-Thinking is a reasoning dataset where the chain-of-thought has been translated from English into one of 4 languages: Spanish, French, Italian, and German. The dataset was created by sampling 1k training samples from the SystemChat subset of SmolTalk2 and translating the reasoning traces with another language model. This dataset was used in the OpenAI Cookbook to fine-tune the OpenAI gpt-oss models. You can load the dataset using: from datasets import… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceH4/Multilingual-Thinking.

The global Game Customer Service Outsourcing market, valued at $743 million in 2025, is projected to experience steady growth, driven by the escalating popularity of online gaming and the increasing demand for high-quality, responsive customer support. The market's Compound Annual Growth Rate (CAGR) of 3.2% from 2025 to 2033 indicates a sustained expansion, fueled by several key factors. The rising complexity of modern games, coupled with the need for multilingual support to cater to a global player base, necessitates specialized outsourcing solutions. Furthermore, the cost-effectiveness of outsourcing customer service compared to in-house teams is a significant driver, allowing game developers and publishers to focus on core game development and other strategic initiatives. The increasing adoption of advanced technologies like AI-powered chatbots and automated ticketing systems is streamlining customer support processes and improving efficiency, contributing to market growth. However, challenges like data security concerns and maintaining consistent service quality across different outsourcing partners remain crucial aspects to address. This growth is expected to be distributed across various segments, including support for mobile games, PC games, and console games, each with its own specific customer service needs. The market is characterized by a mix of large established BPO companies and specialized firms catering exclusively to the gaming industry. Geographical expansion will also play a role, with regions experiencing high growth in gaming adoption likely to show a higher demand for outsourcing services. While data specific to regional breakdown is not available, it is reasonable to anticipate significant growth in regions with large and expanding gaming populations like Asia-Pacific and North America, with Europe and Latin America also contributing substantially. The competitive landscape is dynamic, with companies like GlowTouch, Morph Networks, and Customer Umbrella constantly innovating to stay ahead. The market will likely see increased consolidation and strategic partnerships as businesses seek to expand their reach and service offerings.

Call Center Audio Recordings Dataset: 100,000+ Hours of Customer-Agent Conversations in Multiple Languages

FileMarket AI Data Labs presents an extensive call center audio recordings dataset with over 100,000 hours of customer-agent conversations across a diverse range of topics. This dataset is designed to support AI, machine learning, and speech analytics projects requiring high-quality, real-world customer interaction data. Whether you're working on speech recognition, natural language processing (NLP), sentiment analysis, or any other conversational AI task, our dataset offers the breadth and quality you need to build, train, and refine cutting-edge models.

Our dataset includes a multilingual collection of customer service interactions, recorded across various industries and service sectors. These recordings cover different call center topics such as customer support, sales and telemarketing, technical helpdesk, complaint handling, and information services, ensuring that the dataset provides rich context and variety. With support for a broad spectrum of languages including English, Spanish, French, German, Chinese, Arabic, and more, this dataset allows for training models that cater to global customer bases.

In addition to the audio recordings, our dataset includes detailed metadata such as call duration, region, language, and call type, ensuring that data is easily usable for targeted applications. All recordings are carefully annotated for speaker separation and high fidelity to meet the highest standards for audio data.

Our dataset is fully compliant with data protection and privacy regulations, offering consented and ethically sourced data. You can be assured that every data point meets the highest standards for legal compliance, making it safe for use in your commercial, academic, or research projects.

At FileMarket AI Data Labs, we offer flexibility in terms of data scaling. Whether you need a small sample or a full-scale dataset, we can cater to your requirements. We also provide sample data for evaluation to help you assess quality before committing to the full dataset. Our pricing structure is competitive, with custom pricing options available for large-scale acquisitions.

We invite you to explore this versatile dataset, which can help accelerate your AI and machine learning initiatives, whether for training conversational models, improving customer service tools, or enhancing multi-language support systems.

Retained-Earnings Time Series for Maximus Inc. Maximus, Inc. operates as a provider of government services worldwide. It operates through three segments: U.S. Federal Services, U.S. Services, and Outside the U.S. The U.S. Federal Services segment offers business process services, eligibility and enrollment, outreach, and other services for federal health and human services programs; clinical services; and technology solutions, including application development and modernization services, enterprise business solutions, advanced analytics and emerging technologies, cybersecurity services, and infrastructure and engineering solutions. The U.S. Services segment offers program eligibility support and enrollment; centralized multilingual customer contact centers, multichannel, and digital self-service options for enrollment; application assistance and independent health plan choice counseling; beneficiary outreach, education, eligibility, enrollment, and redeterminations; subsidized telephone services; and person-centered independent assessment services. This segment also provides employment services, such as eligibility support, case management, job-readiness preparation, job search and employer outreach, job retention and career advancement, and educational and training services; technology solutions; system implementation project management services; and specialized consulting services. The Outside the U.S. segment offers BPS and technology solutions for international governments, including health and disability assessments, program administration for employment services, wellbeing solutions and other job seeker-related services, digitally-enabled customer services, and technologies for modernization. Maximus, Inc. was founded in 1975 and is headquartered in McLean, Virginia.

Cost-of-Goods-Sold-Including-Depreciation-and-Amortization Time Series for Maximus Inc. Maximus, Inc. operates as a provider of government services worldwide. It operates through three segments: U.S. Federal Services, U.S. Services, and Outside the U.S. The U.S. Federal Services segment offers business process services, eligibility and enrollment, outreach, and other services for federal health and human services programs; clinical services; and technology solutions, including application development and modernization services, enterprise business solutions, advanced analytics and emerging technologies, cybersecurity services, and infrastructure and engineering solutions. The U.S. Services segment offers program eligibility support and enrollment; centralized multilingual customer contact centers, multichannel, and digital self-service options for enrollment; application assistance and independent health plan choice counseling; beneficiary outreach, education, eligibility, enrollment, and redeterminations; subsidized telephone services; and person-centered independent assessment services. This segment also provides employment services, such as eligibility support, case management, job-readiness preparation, job search and employer outreach, job retention and career advancement, and educational and training services; technology solutions; system implementation project management services; and specialized consulting services. The Outside the U.S. segment offers BPS and technology solutions for international governments, including health and disability assessments, program administration for employment services, wellbeing solutions and other job seeker-related services, digitally-enabled customer services, and technologies for modernization. Maximus, Inc. was founded in 1975 and is headquartered in McLean, Virginia.

Total-Long-Term-Assets Time Series for Maximus Inc. Maximus, Inc. operates as a provider of government services worldwide. It operates through three segments: U.S. Federal Services, U.S. Services, and Outside the U.S. The U.S. Federal Services segment offers business process services, eligibility and enrollment, outreach, and other services for federal health and human services programs; clinical services; and technology solutions, including application development and modernization services, enterprise business solutions, advanced analytics and emerging technologies, cybersecurity services, and infrastructure and engineering solutions. The U.S. Services segment offers program eligibility support and enrollment; centralized multilingual customer contact centers, multichannel, and digital self-service options for enrollment; application assistance and independent health plan choice counseling; beneficiary outreach, education, eligibility, enrollment, and redeterminations; subsidized telephone services; and person-centered independent assessment services. This segment also provides employment services, such as eligibility support, case management, job-readiness preparation, job search and employer outreach, job retention and career advancement, and educational and training services; technology solutions; system implementation project management services; and specialized consulting services. The Outside the U.S. segment offers BPS and technology solutions for international governments, including health and disability assessments, program administration for employment services, wellbeing solutions and other job seeker-related services, digitally-enabled customer services, and technologies for modernization. Maximus, Inc. was founded in 1975 and is headquartered in McLean, Virginia.

Machine Translation (MT) System Market Outlook

The global market size for Machine Translation (MT) Systems was valued at approximately USD 1.1 billion in 2023 and is projected to reach USD 3.5 billion by 2032, growing at a compound annual growth rate (CAGR) of 13.5% during the forecast period. The rapid growth in digital communications and globalization are significant factors driving the market's expansion. In an increasingly interconnected world, the demand for efficient and accurate translation services is escalating. This growth is further powered by advancements in artificial intelligence (AI) and machine learning, which are enhancing the accuracy and functionality of MT systems.

One of the primary growth factors for the MT system market is the surge in cross-border trade and communication. With businesses and individuals engaging in global interactions more than ever before, the necessity for translating diverse languages efficiently has become paramount. This has particularly become crucial for sectors such as e-commerce, where product descriptions, customer service, and marketing materials need to be accessible in multiple languages to cater to a global customer base. Furthermore, the rise in international travel and migration has also fueled the demand for MT systems, aiding in overcoming language barriers and enhancing communication.

Another key growth driver is the continuous improvement and innovation in AI and machine learning technologies. These advancements are significantly enhancing the performance of MT systems, making translations more accurate and contextually relevant. Neural Machine Translation (NMT) systems, in particular, have revolutionized the industry by using deep learning methods to produce translations that are closer to human-like fluency. This technological progress is encouraging more organizations to adopt MT systems, thereby driving market growth.

The increasing adoption of cloud-based technologies is also a vital factor contributing to the market's growth. Cloud-based MT systems offer several advantages, such as scalability, flexibility, and cost-effectiveness, which are highly beneficial for businesses. These systems can be easily integrated with other cloud-based applications, facilitating seamless translation services across various platforms. Moreover, the shift towards remote working arrangements, accelerated by the COVID-19 pandemic, has further emphasized the need for cloud-based solutions, including MT systems, to support global communication and collaboration.

Regionally, North America holds a significant share in the MT system market, driven by the early adoption of advanced technologies and a strong presence of key market players. Europe is also a prominent market due to the high demand for translation services in its multilingual environment. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period, fueled by increasing globalization, a growing e-commerce sector, and significant investments in AI technologies.

Technology Analysis

When examining the MT system market by technology, it is essential to consider the evolution and applications of various methodologies, namely Rule-Based Machine Translation (RBMT), Statistical Machine Translation (SMT), and Neural Machine Translation (NMT). RBMT, one of the earliest forms of MT, relies on linguistic rules and dictionaries to translate text. Although not as prevalent today, RBMT systems are still utilized in specific niche applications where linguistic precision is crucial. These systems require extensive rule development and maintenance but offer high consistency in specialized domains.

SMT, which emerged as a significant advancement over RBMT, uses statistical models derived from bilingual text corpora to generate translations. This approach marked a breakthrough in MT by leveraging large datasets to improve translation quality. SMT systems are particularly effective in handling a wide variety of language pairs and large volumes of text. However, the quality of SMT translations can vary depending on the availability and quality of the training data, leading to challenges in achieving contextual accuracy.

NMT represents the latest and most advanced technology in the MT system market. By utilizing deep learning and artificial neural networks, NMT systems can produce highly accurate and contextually appropriate translations. These systems learn to translate entire sentences as units, capturing more nuanced meaning and context compared to RBMT and SMT. NMT is rapidly becoming