Question: Can you recommend a solution that monitors and alerts me to problems with my large language models in real-time?

If you need a more mature solution to monitor and alert you to issues with your large language models in real-time, Openlayer is a great option. This platform is geared for building, deploying, and managing high-quality AI models, with a particular focus on LLMs. It includes automated testing, monitoring and alerting, so you can quickly identify issues. With versioning and tracking, developer-friendly integration and security compliance, Openlayer is great for data scientists, ML engineers and product managers.

Another option is Athina, an end-to-end platform for enterprise GenAI teams. Athina has real-time monitoring, cost tracking and customizable alerts so you can better keep tabs on output quality and deploy models with confidence. It also includes LLM Observability, Experimentation and Role-Based Access Controls. It's geared for teams that want to speed up their AI development while ensuring it's reliable and efficient.

If you're worried about maintaining high standards of quality and safety in generative AI, LangWatch is a good option. It offers real-time metrics for conversion rates, output quality and user feedback so you can continually improve your models. And with robust guardrails against jailbreaking and sensitive data leakage, LangWatch ensures your AI applications are reliable and faithful, a good option for developers and product managers.

Last, Deepchecks is a good option for automating the evaluation and debugging of LLM applications. It uses a "Golden Set" approach to create a rich ground truth and detect problems like hallucinations and bias. Deepchecks automates monitoring, debugging and version comparison, so you can ensure the quality and reliability of your LLM-based software from development to deployment.