This topic covers platforms and marketplaces that enable AI automation (agents, pipelines, and domain‑specific assistants) to operate with decentralized infrastructure and full user custody—meaning users retain control of their data, cryptographic keys, and where models run. As of 2026‑04‑01 this is timely because enterprises and regulators are pushing for stronger data governance, auditable provenance, and privacy-preserving deployments; on‑chain components promise tamper‑evident logs and composable economic/governance primitives, while self‑hosted or private deployments preserve custody. Key tools illustrate the landscape: StackAI and Lindy are no‑code/low‑code platforms for designing, deploying, and governing autonomous agents in enterprise contexts; Xilos positions itself as an “intelligent agentic” infrastructure offering enterprise visibility into connected services and agent activity; Tabnine and JetBrains AI Assistant represent developer‑centric, privacy‑focused copilots optimized for private/self‑hosted deployments and in‑IDE context; Qodo (formerly Codium) focuses on quality‑first code review, test generation, and SDLC governance across repos; Bookeeping.ai demonstrates verticalized automation where custody and secure API connections matter for financial data. Adoption hinges on hybrid on‑chain/off‑chain architectures: on‑chain for verifiability, orchestration, and marketplace settlement; off‑chain for low‑latency model execution and private data handling. Practical considerations include key management, secure enclaves or MPC for private inference, cost and latency tradeoffs, and standards for provenance and governance. Together these tools and approaches form a pragmatic path for organizations that need automated, agentic workflows with auditability and retained custody rather than surrendering sensitive assets to third‑party cloud services.