Question: Looking for a natural language question answering platform that can provide accurate and contextually relevant answers to our business-critical questions.

If you're looking for a natural language question answering platform that can give you contextually relevant and accurate answers to your business-critical questions, Perplexity is a great option. It uses AI models like GPT-4o, Claude-3 and Sonar Large (LLaMa 3) to generate answers in real-time across multiple languages. It includes unlimited quick searches, file upload and analysis, and customizable models that can be trained to your needs. Perplexity also offers premium features like Pro Search and Thread History, making it a good option for individuals and professionals who need authoritative information.

Another good option is Glean, which uses Retrieval Augmented Generation (RAG) technology to generate answers based on your company's data. It builds a knowledge graph that links all enterprise data, enabling advanced personalization of answers. Glean is geared for teams like engineering, support and sales, giving them quick access to the right information and cutting down on the number of questions they have to ask.

Expert.ai is another platform worth considering, which is designed to turn text data into knowledge and insights using deep NLP. It uses a combination of symbolic and machine learning approaches for high accuracy and flexibility. Expert.ai is particularly well-suited for industries like insurance, pharmaceuticals, publishing and financial services, helping companies make more informed decisions and increase productivity through intelligent document processing and domain language models.

Last, ThoughtSpot offers an AI-powered analytics platform that lets users ask complex data questions in natural language and get answers. It offers embedded analytics, flexible data modeling and natural language queries, making it good for a wide range of industries. The platform is designed to scale and modernize analytics, helping companies make data-driven decisions more efficiently.