Trainkore is a versatile platform that automates prompt generation, model switching, and evaluation to optimize performance and cost-efficiency. With its model router feature, you can choose the most cost-effective model for your needs, saving up to 85% on costs. It supports dynamic prompt generation for various use cases and integrates smoothly with popular AI providers like OpenAI, Langchain, and LlamaIndex. The platform offers an observability suite for insights and debugging, and allows prompt versioning across numerous renowned AI models.

Agent Control Plane offers a centralized control plane for designing, orchestrating, and operating autonomous AI agents at scale. Developers can configure agent behaviors via declarative definitions, integrate external services and APIs as tools, and chain multi-step workflows. It supports containerized deployments with Docker or Kubernetes, real-time monitoring, logging, and metrics through a web-based dashboard. The framework includes a CLI and RESTful API for automation, enabling seamless iteration, versioning, and rollback of agent configurations. With an extensible plugin architecture and built-in scalability, Agent Control Plane accelerates the end-to-end AI agent lifecycle, from local testing to enterprise-grade production environments.

Neum AI provides an advanced framework for constructing data infrastructures tailored for Retrieval Augmented Generation (RAG) and Semantic Search applications. This cloud platform features distributed architecture, real-time syncing, and robust observability tools. It helps developers quickly and efficiently set up pipelines and seamlessly connect to vector stores. Whether you're processing text, images, or other data types, Neum AI's system ensures deep integration and optimized performance for your AI applications.