AIxBlock

According to its website, AIxBlock helps enterprise AI teams access real-world datasets and large-scale custom data across modalities, industries, and use cases. Its speech services cover collection, transcription, and annotation in 100+ languages using a global crowd. Its text and dialogue services include conversation annotation, intent and entity labeling, RLHF-style preference data, and LLM fine-tuning datasets. It offers an off-the-shelf library of hundreds of thousands of hours of call center audio with US, India, and Philippines accents. A Self-Hosted Platform lets clients connect their own storage so data is delivered directly to them, and the company states it does not keep copies. The site describes quality controls such as consensus mechanisms, blind tests, multi-tier QC, and multi-layer contributor verification. It states it has seven years of experience, has delivered projects for Fortune 100 companies and unicorns including Oracle, AWS, Apple, and Uber, and is backed by EU innovation funding. The site also presents case studies covering banking PII/PCI identification, two-party conversational speech data, and multi-locale audio programs with reported accuracy figures.

Key features

• Speech data collection, transcription, and annotation in 100+ languages
• Sound and environment audio collection for classification and noise detection
• Text and dialogue data services including conversation annotation and intent/entity labeling
• RLHF-style preference data for model alignment
• LLM fine-tuning datasets for specific industries or domains
• Off-the-shelf call center audio library with hundreds of thousands of hours
• Self-Hosted Platform with data engine, training, and GPU marketplace
• Option to connect client storage so data is not held by AIxBlock
• Multi-layer contributor verification including KYC and biometric checks
• Layered quality controls including consensus, QC, blind tests, and audits
• 24/7 worker support and client feedback channel
• Local SME guideline localization and training in local languages

Best suited for

• Enterprise AI teams building speech and voice AI models
• Organizations needing multilingual speech or audio training data
• Foundation model labs and product teams fine-tuning or aligning LLMs
• Regulated organizations such as banking, healthcare, and government with data sovereignty needs
• Teams needing call center audio datasets for speech analytics or QA

Pricing

Not stated on the website