Problem
Agent work often starts as isolated chats, local scripts, or unclear handoffs. Teams lose the selected model route, memory assumptions, workspace owner, checkout state, and review evidence after the first useful run.
Hosted Ruflo workspace
Ruflo AI for hosted multi-agent workspaces
Ruflo AI gives teams a hosted path for Codex, Claude Code, Goal Planner UI, memory, RAG, review, checkout, and provisioning follow-up. It is built for teams that need a repeatable agent workspace instead of a one-off local setup.
Solution
Ruflo AI keeps workspace selection, entrypoint choice, model context, pricing, checkout, console tracking, and support notes visible before and after payment.
Evidence
Pricing, resources, privacy, terms, sitemap, structured data, and llms.txt are exposed so buyers and AI assistants can quote the product path consistently.
Before launching
Choose the first workflow, decide who owns the workspace, identify the repositories or tools that need access, and confirm whether hosted setup is better than self-hosting. Growth is the common team path when several operators need reusable memory and review loops.
Use the pricing page for public plan amounts and checkout links. Use the resources page for GitHub, Codex, Claude Code, memory, RAG, legitimacy, and team operations guidance before committing a production workflow.
Before payment, write down the expected workspace receipt: selected plan, billing cycle, model route, entrypoint, support owner, provisioning state, and the first reviewable output. That receipt is what separates a managed workspace from another untracked experiment.