100+ agents. One swarm. Self-learning memory. We set up Ruflo, Hermes, OpenClaw, and Claude Code — all orchestrated from one dashboard. Like hiring a tech department for £199.
Enterprise tier includes Ruflo agent swarm — 100+ agents, self-learning memory, federation. See our 8 running agents →
Multi-agent orchestration is the coordination of multiple AI agents working together to achieve a common goal. Instead of relying on a single agent to handle every task, a fleet of specialised agents each handles a specific part of the workflow, passing information between them as needed.
For example, in a lead generation workflow, one agent might scrape potential leads from the web, another might enrich the data with company information, a third might score the leads by quality, and a fourth might draft personalised outreach emails. Each agent does what it does best, and the orchestrator ensures they work together seamlessly.
This approach has several advantages over single-agent systems. It is more resilient — if one agent fails, the others can continue. It is more scalable — you can add more agents to handle increased workload. And it is more capable — each agent can be specialised for a specific task, rather than being a generalist that does everything adequately but nothing exceptionally.
The AI Suite multi-agent fleet includes agents built on several leading AI platforms, each chosen for its specific strengths:
One of the most powerful features of the AI Suite multi-agent fleet is the self-learning memory system. Every task completed by an agent is stored in a shared memory bank, which agents can access to learn from past experiences.
This means that the fleet gets smarter over time. If an agent encounters a problem it has solved before, it can recall the solution and apply it immediately. If an agent makes a mistake, the fleet learns from it and avoids repeating the same error.
The self-learning memory system also enables agents to build on each other's work. If one agent discovers a more efficient way to complete a task, that knowledge is shared with the entire fleet, improving performance across the board.
The Goal Planner is a natural language interface that allows you to define complex goals in plain English. You type what you want to achieve, and the Goal Planner breaks it down into a series of agent tasks, assigns each task to the most appropriate agent, and schedules them for execution.
For example, you might type "Research the top 10 AI tools for UK tradesmen, write a comparison article, and publish it to the blog." The Goal Planner would break this into research, writing, and publishing tasks, assign them to the appropriate agents, and execute them in the correct order.
The Goal Planner makes it possible to deploy a fleet of AI agents without any technical knowledge. You do not need to write code, configure workflows, or understand the underlying technology. You just describe what you want, and the agents make it happen.
A multi-agent system is a collection of AI agents that work together to accomplish a task. Each agent has a specific role — researcher, writer, editor, publisher — and they coordinate their efforts to produce a result that is greater than the sum of its parts. Think of it as a team of specialists, each doing what they do best.
Agent federation is the technology that allows agents on different projects to work together. An agent working on your content marketing can share insights with an agent working on your SEO, creating a feedback loop that improves both. This is the key advantage of a multi-agent system over a collection of isolated tools.
The self-learning memory system is what makes multi-agent orchestration truly powerful. Every task, every result, every error is stored in a memory layer that the agents can access. Over time, the system learns what works and what does not, and adjusts its behaviour accordingly. The result is a system that gets smarter with every task it completes.
Our multi-agent fleet is already running for real businesses. The content drafter produces SEO-optimised articles every morning. The news monitor scans 50+ sources for relevant stories. The site checker monitors uptime and performance. The trend scanner identifies emerging opportunities. All of this happens automatically, 24/7, without human intervention.
The Growth Fleet at £199 is the most popular option for businesses that want to see multi-agent orchestration in action. It includes Hermes, OpenClaw, and Claude Code, all configured and integrated with a 1-hour walkthrough. Most customers see immediate value from the first day.