Answer questions
Customer questions, internal how-tos, policy lookups — grounded in your Knowledge Hub, never generic.
Support · Internal helpdesk
The Agent Greenhouse
Where your AI Operating System comes to life
Knowledge alone is just a smart filing cabinet. Agents read your knowledge, talk to each other, plug into your tools, and get real work done — turning your AI Operating System from an idea into a living system.
Meet your agents
An AI Teammate
A Dandelion agent reads from your Knowledge Hub, uses the tools you already run, and gets real work done. Here's the shape of work they commonly take on.
Execute real work
Draft, send, update, schedule, run workflows. The agent does the task — not just advises on it.
Sales · AI Voice Agents · Workflow runners
Orchestrate other agents
Dispatcher agents delegate across your AI team, escalate to humans, and keep work moving end-to-end.
Operations · Recruiting · Project managers
Watch & surface
Monitor systems, spot gaps in your knowledge, flag anomalies, and proactively surface what matters.
Memory Manager · System monitors
Why our agents are different
Three things set a dandelion agent apart
Most AI agents today are thin wrappers on an LLM. Ours are grounded, connected, and futureproof — by design.
Rooted in your knowledge
Every agent reads from your Knowledge Hub — scoped, permissioned, grounded. Answers come from your business, not the open internet.
Working together, not restricted
Agents delegate to each other. Support escalates to Sales; Ops hands a refund to a Task Agent. Real teamwork, not isolated tools.
Built on open standards
Two open protocols (A2A and MCP) make your AI OS compatible with everything in the ecosystem and locked into nothing.
How open standards workHow it gets built
Your Trusted AI Partner
Frequently Asked Questions
What exactly is an "agent" in The Dandelion?
An agent is a named unit of AI with a job — a role, a memory scope, a set of skills, and clear permissions for who it answers to. Agents can chat with users, execute real workflows, and delegate to each other. Think of them as specialized teammates, not a single chatbot.
How is A2A different from function calling?
Function calling exposes raw tools to an LLM. A2A exposes skills — clean, human-friendly capabilities — and each child agent manages its own tools internally. It's the difference between "use this API" and "ask this teammate."
Can agents connect to the tools we already use?
Yes. We use open standards — MCP for data and tools, A2A for inter-agent communication — so your agents can plug into systems you already run. If a tool has an API or even just a web UI, our team can bring it into your AI Operating System.
What about approvals and MFA?
Agents can pause in an awaiting-input state. A human approves, provides an MFA code, or signs off on a plan before the agent continues. Built in, not bolted on.
Can I bring my own agent?
Yes. Any A2A-compliant agent can plug into the greenhouse and delegate to or receive delegations from your other agents — and we handle the integration, scoping, and permissions work as part of the partnership.
Ready to find a real AI partner?
Book a discovery call. We'll learn your business, design the agents that belong in it, and walk you through what the partnership looks like from day one.