Enterprise AI agent platforms for workflow integration refer to systems and ecosystems that let organizations build, orchestrate, deploy and govern autonomous or semi‑autonomous AI agents as part of day‑to‑day business processes. As of 2026‑02‑25 this space centers on three converging needs: reliable multi‑agent orchestration across services, low‑code integration into existing workflow systems, and enterprise controls for observability, privacy and compliance. Key vendor patterns include no‑code/low‑code platforms (StackAI, Relevance AI) that accelerate agent creation and deployment; engineering frameworks (LangChain and LangGraph) that provide state management, testing and debug tooling for agentic apps; cloud ML platforms (Vertex AI) and model providers (Mistral AI) that supply managed model runtimes and fine‑tuning; and specialist governance/validation tooling (Monitaur) to centralize policy, monitoring and vendor risk. Kore.ai and Yellow.ai illustrate enterprise‑focused agent platforms emphasizing multi‑agent workflows, channel integration and CX/EX automation. AutoGPT and similar open projects demonstrate rapid experimentation with autonomous agents, while marketplace and vendor initiatives (OpenAI Frontier Alliance, Workday Agent Builder, Oracle Agents) are shaping distribution, certification and enterprise integrations. Important trends: composable multi‑agent workflows are moving from research to production, driving demand for standardized observability, policy enforcement and model choice across hybrid deployments; low‑code tooling is lowering the barrier to embed agents into ERP/HR/CRM workflows; and marketplaces and alliance programs are emerging to simplify procurement and interoperability. For enterprise buyers this means evaluating platforms not only on agent capabilities, but on governance, integration with existing workflow platforms, lifecycle management, and the ability to run or certify preferred models under regulatory constraints.