About Raltic
Raltic is building the shared operating layer for teams that use AI agents every day. Local and cloud agents can work in the same workflow rooms, while people retain evidence, task ownership, review, and the final decision.
Why we exist
Teams now use several models, coding agents, connected tools, and private chat sessions. The operational problem is no longer access to an answer. It is knowing what was requested, what evidence an agent used, who owns the next task, whether a person reviewed the result, and what the team should remember.
Raltic organizes that work around bounded workflow rooms rather than a generic assistant. The product is deliberately honest about runtime, permission, and data boundaries because trust depends on describing what each layer actually controls.
Start with a repeatable process and a reviewable artifact before adding agents or triggers.
Prefer sources, artifacts, diffs, tests, and explicit gaps over fluent unsupported conclusions.
Agents prepare and propose. People remain responsible for consequential product, engineering, customer, and business decisions.
Use verified Claude Code and Codex bridge runtimes alongside managed cloud agents without forcing one provider model.
Current product
Web workspace, local bridge, desktop beta, cloud agents, tasks, run state, workspace memory, and GitHub, Linear, and Notion connectors.
Verified runtimes
Claude Code and OpenAI Codex. OpenClaw and Hermes remain experimental and are excluded from production-ready claims.
Research standard
Comparison and educational content links to current first-party or standards sources, carries update dates, and states when a competing product is the better fit.