Conversational AI
Enterprise Conversational AI Technology Built on Trusted Data
Our conversational AI solutions are designed for real-world performance, supporting the full conversational stack, from data to deployment.
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Conversational AI Services You Can Trust at Scale
High-quality conversational data powering speech recognition, AI chatbots, and virtual assistants in real-world environments.
Diverse speech data for real‑world scenarios
Spontaneous H2H and IVR dialogues, scripted monologues, and live audio from calls, meetings, and podcasts.
Rich transcriptions and annotations
Capture tone, intent, and context for training robust ASR and NLU models.
Multilingual chatbot expertise
Accelerat.ai project supports high‑ and low‑resource languages for inclusive AI.
End‑to‑end tech stack guidance
Speech‑to‑text, text‑to‑speech, NLU/NLG engines, and dialogue management frameworks.
Operational ROI focus
Reduce resolution times, improve service quality, and scale capacity for peak demand.
Trusted consortium partnerships
Government, enterprise, and academic collaboration for resilient solutions.
Conversational AI Solutions across any data type
High-quality conversational AI solutions across text, speech, image, video, and multimodal data, built for scalable and compliant AI systems.
Audio Annotation
Build and evaluate speech data for conversational AI:
Spontaneous Speech (H2H): Two‑person dialogues representative of call center interactions.
Spontaneous Speech (IVR): Human‑machine exchanges with TTS prompts and natural responses.
Scripted Speech: Monologues for controlled acoustic and linguistic coverage.
Live Data: Real recordings from meetings, interviews, podcasts, and lectures.
Rich Transcriptions: Detailed annotations for tone, intent, and speaker metadata.
Trusted by Leading AI innovators
Conversational AI Use Cases Across Industries
Practical conversational AI use cases where our conversational AI solutions, data, and expertise enable smarter, multilingual dialogue systems across voice and text. See more use cases
Build safer platforms with expertly annotated data for text, image, and video moderation.
Train and evaluate ASR models with diverse, high-quality multilingual audio datasets.
Power transcription, summarization, and insights with real-world meeting data.
Proven Trust. Real Impact.
Real feedback from AI teams and enterprises using Defined.ai to power accurate, reliable, and scalable models.
The off-the-shelf datasets from Defined.ai have been a game-changer for us. The data provided has significantly improved our ML models, bringing us one step closer to expanding into the LATAM and US markets. Whenever we need high-quality data, Defined.ai will always be our first choice and trusted partner!
Learn more about Conversational AI
Explore blogs, case studies, and expert guides on speech data, multilingual chatbot design, and evaluation best practices.
Case Study: Building High-Performing Multilingual Conversational AI for Global Dialogue Systems
Insights into how tailored multilingual datasets and evaluation practices improve conversational AI quality and real-world user experiences.
Please Hold: AI in Call Centers and the Future of Customer Care — Trends, Tech, and Strategic Roadmaps
A deep dive into how AI and automation transform customer service operations, enhance agent workflows, and elevate customer satisfaction.
Multilingual Conversational AI Explained: Challenges, Benefits, and Best Practices for Global Interactions
Explore how conversational AI adapts across languages, strengthens inclusivity, and delivers seamless user experiences at scale.
Case Study: Building High-Performing Multilingual Conversational AI for Global Dialogue Systems
Insights into how tailored multilingual datasets and evaluation practices improve conversational AI quality and real-world user experiences.
Please Hold: AI in Call Centers and the Future of Customer Care — Trends, Tech, and Strategic Roadmaps
A deep dive into how AI and automation transform customer service operations, enhance agent workflows, and elevate customer satisfaction.
Multilingual Conversational AI Explained: Challenges, Benefits, and Best Practices for Global Interactions
Explore how conversational AI adapts across languages, strengthens inclusivity, and delivers seamless user experiences at scale.
FAQ About Our Conversational AI Solutions
Get clear answers on how our Conversational AI solutions deliver smarter, more personalized customer experiences. Explore the full FAQ
Conversational AI uses machine learning, natural language processing (NLP), and speech technologies to understand, interpret, and respond to human language in a natural and contextaware way. Unlike rule-based chatbots that rely on pre-scripted responses, Conversational AI systems can handle open-ended queries, maintain context, personalize interactions, and learn over time.
Training Conversational AI requires high-quality labeled datasets, including:
- Speech data: Conversations, command prompts, IVR interactions, emotional tone recordings
- Text data: Transcripts, Q&A, intent-labeled messages, sentiment-rich content
- Multilingual datasets: Voice and text samples across diverse languages, dialects, and accents
These datasets help models understand natural language, intent, sentiment, tone, and context.
Defined.ai sources contributors from 150+ countries and 500+ languages/dialects, ensuring representation across age groups, regions, genders, and cultures. During collection and annotation, datasets undergo bias detection and fairness checks, helping enterprises build more inclusive and accurate conversational systems.
Yes. All projects follow ISO-certified processes and meet GDPR and HIPAA requirements. This ensures:
- Secure data handling and storage;
- Privacy protection for contributors;
- Compliance with global regulations;
This is especially critical for industries like healthcare, finance, and government.
Absolutely. With a vetted global crowd of 1.6M+ contributors, Defined.ai delivers millions of speech and text samples at scale, with:
- Real-time project monitoring;
- Multi-layer quality validation;
- Domain-specific customization;
This enables enterprises to build conversational systems that perform consistently in real-world, multilingual environments.
Most conversational AI models are over-optimized for English, leading to poor performance in global markets. Defined.ai bridges this gap by providing high-quality training data for low-resource languages and specific regional dialects, ensuring your models are truly inclusive and globally scalable.