RedOS agents have HeartBeats: scheduled check-ins — morning briefings, weekly reviews, quarterly planning — that pull in your calendar, tasks and metrics and reach out first, without being asked.

Every agent draws on Red Core, your organisation’s living knowledge base, in real time — strategy, customer intelligence, operating metrics. They answer from current truth, not stale training data. Their work feeds back in, so the system compounds: the more your agents work, the smarter every agent gets.

Two modes. Private (1:1): one person, fully isolated memory, confidential by default. Shared (Team): a whole group, group-visible, automatically feeding the organisation’s knowledge base.

Every agent carries a budget. When it's spent, the agent pauses and requests approval — no surprises. Owners see spend against budget in real time. This is how a 50-person company runs AI at scale without anyone running up a five-figure bill.

Each agent gets a name, a personality and a face. You talk to Marcus, your marketing strategist — not 'agent-uuid-123' — over chat, a dedicated workspace, Telegram or email. Team members, not terminal windows.

Tiered routing — quality, balanced, fast, cheap — set per agent. Your executive coach runs on the best model; your data-cruncher runs fast and cheap. A better model launches tomorrow? Swap the config, not the agent. No vendor lock-in.

Build agents, workflows and data listeners visually in Red Forge, with an AI co-pilot. An approval workflow gates every deployment before it ever touches a user.

Red Command gives you one surface for your entire AI workforce: every agent, who it's assigned to, what it's spending, when it last checked in, what it's working on. The difference between a developer's experiment and a managed AI workforce.