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Explore the key features that make Shakudo powerful for multi-agent builders workflows.
Shakudo abstracts away the complexity of managing Kubernetes infrastructure while providing a pre-integrated catalog of 170+ AI and data components that are configured to work together. When running frameworks like LangChain or CrewAI directly on Kubernetes, teams must handle container orchestration, networking, dependency management, security hardening, monitoring, and inter-service communication themselves. Shakudo provides much of this through its unified control plane, along with built-in RBAC, vulnerability scanning, and governance dashboards, allowing teams to focus on building AI applications rather than maintaining infrastructure.
Shakudo's public website describes the platform as SOC 2 Type II certified and engineered for enterprise security standards. The platform includes automatic mitigation of OWASP Top 10 LLM risks, built-in role-based access control (RBAC) linked into stack components, container image vulnerability scanning, and PyPI/CRAN package vulnerability scanning. It supports deployment in air-gapped networks and private cloud environments, and the product positioning emphasizes keeping data within the customer's own infrastructure.
Shakudo supports both public cloud and on-premises deployments. For public cloud, it deploys within the customer's own VPC on AWS, GCP, or Azure. For organizations with stricter requirements, it also supports on-premises and private cloud deployments, including air-gapped network environments.
Beyond the core infrastructure platform, Shakudo provides several purpose-built AI applications: Patina for autonomous cross-department workflows with auditability, Kaji as an AI expert assistant for enterprise use, an AI Gateway serving as a unified control plane to govern AI model usage, an autonomous multi-agent platform, an MCP Proxy for connecting existing APIs to AI systems, Extract Flow for secure document data extraction, and specialized modules for knowledge graph construction, workflow automation, vector database deployment, text-to-SQL, and reverse ETL.
Shakudo serves a range of regulated and data-intensive industries including financial services, healthcare and life sciences, aerospace, automotive and transportation, climate and energy, manufacturing, real estate, and retail. Public product material lists use cases including assessing investment thesis fit and drift in finance, extracting key insights from financial documents, creating and managing SOPs with AI automation, generating real-world evidence for healthcare decisions, optimizing ticket pricing with dynamic demand modeling, and scheduling preventive maintenance for energy infrastructure.
Shakudo offers guided demos, AI workshops, and proof-of-concept engagements through its sales process. There is no self-serve free tier or public fixed-price plan listed in the available product material, so prospective customers should contact Shakudo to discuss scope, deployment requirements, and pricing.
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Tutorial updated March 2026