About NLP Cloud
NLP Cloud is a state-of-the-art artificial intelligence platform designed to provide users with access to cutting-edge AI engines. The platform emphasizes data privacy, ensuring that businesses can utilize AI without compromising confidentiality. NLP Cloud offers a range of AI engines, from specific ones to advanced generative models, all aimed at seamless integration into applications at a cost-effective rate.
Features of NLP Cloud
- High Performance: NLP Cloud boasts fast and accurate AI models that are optimized for production. The platform leverages advanced hardware to provide a highly available inference API.
- Data Privacy and Security: The platform is compliant with HIPAA, GDPR, and CCPA standards. It prioritizes user data privacy, ensuring that the data is neither stored nor used for training their AI models.
- On-Premise Deployment: For those with critical security and privacy needs, NLP Cloud allows the deployment of models in-house on isolated servers.
- Multilingual AI: NLP Cloud supports AI models in over 200 languages, thanks to its multilingual models and addons.
- Simplicity: Users don’t have to worry about DevOps or API programming. The platform allows users to focus solely on text processing, ensuring quick project delivery.
- Custom Models: Users can fine-tune their models or upload custom models for easy deployment to production.
- Collaboration with NVIDIA: NLP Cloud collaborates with NVIDIA to ensure top-notch performance. Their generative AI engines are deployed on advanced NVIDIA GPUs for low latency and cost-effectiveness.
- Built for Developers: NLP Cloud offers a robust and straightforward API. It manages scalability and high availability seamlessly.
- Support: The platform provides extensive support, including client libraries on Github and a dedicated support team for guidance on using generative AI and large language models.
- Custom Model Training: Users can upload, train, or fine-tune their AI models with their data. This feature allows for immediate deployment to production without concerns about deployment specifics like RAM usage or scalability.