AfterQuery

AfterQuery provides a data platform engineered for developers to build, evaluate, and monitor generative AI applications. The company's offerings are structured to streamline the entire lifecycle of Large Language Model (LLM) application development. Its services are centered around three main pillars: data preparation for Retrieval-Augmented Generation (RAG), model evaluation, and application monitoring.

The platform enables the connection to various enterprise data sources such as Notion, Slack, and databases, preparing the data for use by LLMs. For evaluation, it offers tools to test LLM applications using both qualitative and quantitative metrics to ensure reliability before deployment. Once in production, AfterQuery provides observability features to monitor the application's performance, track costs, and identify issues like hallucinations or prompt drift, ensuring consistent and dependable operation.

Founded by Michael C. and Robert M., AfterQuery is a Y Combinator-backed company. It targets developers and organizations looking to implement production-ready LLM-powered applications, addressing the critical need for robust data management and performance oversight in the rapidly evolving generative AI landscape. The business model is likely subscription-based, offering access to its comprehensive suite of development tools.

Keywords: Generative AI applications, LLM development platform, Retrieval-Augmented Generation, RAG, LLM evaluation, LLM observability, data preparation for AI, AI model monitoring, prompt engineering, AI development tools, Y Combinator, enterprise AI, application performance, data-centric AI