Best Agentic Orchestration Platforms for Enkrypt AI

Agents operating in a demonstration setting require consistent, regulated workflows before transitioning to a production environment. Anaconda AI Orchestration transforms agent and AI initiatives into accountable workflows that seamlessly progress from development to production across various platforms, including cloud, hybrid, on-premises, and sovereign settings. It effectively monitors models, lineage, artifacts, resources, and costs throughout the process. This orchestration is grounded in Metaflow, a framework developed at Netflix. Additionally, Enkrypt AI from Anaconda conducts red teaming on agents and their MCP connections prior to deployment, manages agent access to tools and data through established policies, and enforces runtime guardrails. Developers utilize Kilo by Anaconda to create the agents, leveraging a library of over 500 models and reliable MCPs sourced from AI Artifacts.

The Model Context Protocol (MCP) is a flexible, open-source framework that streamlines the interaction between AI models and external data sources. It enables developers to create complex workflows by connecting LLMs with databases, files, and web services, offering a standardized approach for AI applications. MCP’s client-server architecture ensures seamless integration, while its growing list of integrations makes it easy to connect with different LLM providers. The protocol is ideal for those looking to build scalable AI agents with strong data security practices.