Almeta ML leverages advanced machine learning algorithms to predict potential customer actions based on their previous behaviors. Users can calculate metrics such as the propensity to purchase, receive personalized product recommendations, and determine the best times to engage customers. These predictions enable businesses to tailor their marketing strategies effectively, increasing conversion rates and optimizing ad spend. The platform is user-friendly, allowing easy integration with websites, and provides real-time analytics to refine marketing approaches.

Granite Retrieval Agent provides developers with a flexible platform to build retrieval-augmented generative AI agents that combine semantic search and large language models. Users can ingest documents from diverse sources, create vector embeddings, and configure Azure Cognitive Search indexes or alternative vector stores. When a query arrives, the agent retrieves the most relevant passages, constructs context windows, and calls LLM APIs for precise answers or summaries. It supports memory management, chain-of-thought orchestration, and custom plugins for pre- and post-processing. Deployable with Docker or directly via Python, Granite Retrieval Agent accelerates the creation of knowledge-driven chatbots, enterprise assistants, and Q&A systems with reduced hallucinations and enhanced factual accuracy.