TL;DR
An architectural design that solves complex tasks by combining multiple interacting tools, retrievers, and specialized AI models rather than relying on one monolithic model.
Unlike singular foundation models, compound AI systems rely on structured workflows that integrate diverse digital components. Developers can design systems that execute multi-step chains, call external databases, and deploy specialized neural models for individual pipeline stages. This system-level engineering approach offers greater flexibility, better safety controls, and lower inference costs than a single giant model.
Why this matters for your business
This system-oriented approach allows companies to build reliable, domain-specific AI applications that outperform massive standalone models at a fraction of the operating cost.
