Your AI performance stack is Fireworks + Voyage AI

Fireworks announced a partnership with Voyage AI by MongoDB that makes Voyage’s embedding, multimodal retrieval, and reranking models available natively on its inference platform alongside open models for post-training and serving. The integration is intended to let teams run embedding, retrieval, reranking, and generation through one API and infrastructure environment, reducing separate vendor connections, latency hops, and data-handling boundaries. The post argues that retrieval quality is central to AI systems built on proprietary data, and presents specialized post-trained open models plus data grounding through retrieval as complementary components of business-specific AI. Available Voyage models include voyage-4-large, voyage-4, voyage-4-lite, voyage-4-nano, voyage-multimodal-3.5, and rerank-2.5, with suggested applications ranging from customer support and internal knowledge assistants to agentic workflows, multimodal RAG, semantic search, recommendations, and deduplication. Fireworks states that Voyage 4 Large leads several competing embedding models in its cited average retrieval-quality comparison and directs users to its cookbook and account signup process to build an integrated pipeline.

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