Question: I'm looking for a solution that uses generative AI and neural networks to build large language model apps and predictive systems.

If you're looking for a more complete package to build large language model apps and predictive systems with generative AI and neural networks, Abacus.AI is worth a serious look. The company's suite of products includes ChatLLM for building end-to-end RAG systems, AI Agents for automating complex workflows, and predictive abilities like forecasting and anomaly detection. It also offers customization and a range of tools for modeling and workflow automation, so it's geared for big enterprise operations.

Another top contender is Lamini, an enterprise-focused platform to build, manage and run Large Language Models on your own data. It's got options for memory tuning for high accuracy, deployment on different environments and high-throughput inference. Lamini handles the full model lifecycle, from training to deployment, and can be installed on premise or in the cloud.

If you want to handle the life cycle of large language model-powered applications, Vellum offers a range of tools for prompt engineering, semantic search and monitoring. It's designed for complex workflows, document analysis and chatbots, and comes with options like SOC2 Type II and HIPAA compliance that make it a good option for secure and scalable enterprise use.

Last, Humanloop offers a collaborative platform to manage and optimize Large Language Model applications. It's designed to address common pain points like suboptimal workflows and manual evaluation with tools for collaborative prompt management, evaluation and monitoring. It supports common LLM providers and offers SDKs for easy integration, so it's a good option for product teams and developers looking to improve efficiency and reliability in AI development.