Question: I'm looking for a way to test and train custom AI features with fine-grained data context, do you know of a tool that can do this?

If you want to experiment and train your own custom AI features with fine-grained data context, Airtrain AI is a great option. This no-code compute platform is geared for data teams that need to manage large data pipelines and has built-in tools for large language models (LLMs). With its LLM Playground, Dataset Explorer, and AI Scoring, you can fine-tune models for your specific use case. The platform also has community support and a variety of pricing options depending on your needs.

Another option is Abacus.AI, which lets developers build and run large-scale AI agents and systems with generative AI and neural network technology. The platform can fine-tune LLMs and has predictive and analytical features like forecasting, anomaly detection and language AI. It also has tools for automating complex workflows and integrating multiple data sources, so it's a good option for building your own custom AI agents.

If you're looking for a collaborative platform, Humanloop is designed to optimize LLM app development by solving common problems like inefficient workflows and manual evaluation. It has a collaborative prompt management system, evaluation and monitoring suite, and tools for fine-tuning models. Humanloop supports popular LLM providers and has Python and TypeScript SDKs for easy integration, so it's good for product teams and developers.

Last, Predibase is a low-cost platform for fine-tuning and serving LLMs. You can fine-tune open-source models for your own tasks with advanced techniques. The platform also has a low-cost serving infrastructure, free serverless inference, and enterprise-grade security, so it's a good option for those who need a scalable and secure solution.