Recruit an agent
Open Agents to browse the gallery, organized by area (marketing, sales, e-commerce, personal assistant, and more). Each agent describes what it’s good at and which connections it needs.1
Pick an agent
Find one that matches the job — a data analyst, a document analyzer, a
security checker.
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Put it to work
Start a conversation and brief it. Results appear inline.
Build a custom agent
When no standard agent fits, create your own. A custom agent takes:- Instructions — what it should do, how to behave, what to prioritize.
- Reference documents — files it should always have on hand.
- Pinned skills — reusable skills it can call.
One agent, many deployments
An agent is the durable worker: its name, instructions, knowledge, skills, and run history live in one place. A deployment is a way for people to reach that agent. The same agent can work in Erdo, talk on a phone call, or appear on a website through chat, voice, and video without becoming several disconnected copies. Open Agents → Deployments to see every website, voice-runtime, and phone deployment. Website deployments own only channel settings such as greeting, voice, appearance, allowed origins, usage limits, and meeting scheduling. Edit the agent to change its name or instructions; every attached deployment picks those changes up automatically. External website visitors can search only knowledge your organization has explicitly marked Public — an agent’s private memories and internal skills are never exposed just because it is deployed.- Choose Website to attach an existing agent to an embeddable chat, voice, or video surface. See Website Widget.
- Choose Voice or phone to open a guided chat that casts the voice and can assign a dedicated inbound number. See Voice Calls.
Configure and teach
Every agent has a Knowledge panel where it accumulates what it learns about your business — useful findings, known limitations, and optimizations — and reuses them on future runs. See Knowledge for how this works across your workspace.Some agents need a specific connection to do their job — for example, an
agent that books meetings needs Google Calendar connected. The agent will tell
you what’s missing if a connection is required.
Choose the model
Agents pick the right model for each task on their own — a quick lookup runs on a fast model, a page build on a strong one. When it matters, you can also choose: say the model in the conversation (“build this page with Claude”, “generate three versions and use a different model for each”) and the agent pins it for that piece of work. The model it used is recorded on every run, so you can see which model produced which result and compare them side by side.Model choice affects credit spend — flagship models cost more per run than
fast ones. If model selection isn’t enabled for your workspace yet, the agent
will say so and use the platform default.
What agents can do
Agents use tools to act: query a dataset, run code, search the web, build a page, send an email, or place a phone call. They choose the tools a job needs — you don’t wire them up. Anything that changes your data or reaches outside Erdo goes through review and approval.Seeing what a run used
A long piece of work — a multi-page build, a campaign setup — is rarely one agent acting alone. The agent you are talking to follows skills (reusable playbooks) and hands parts of the job to specialist agents, and the conversation says so as it goes, so you can tell what is driving a step before you decide whether to steer it:- Loaded … at the top of a reply lists the skills, memories, datasets and integrations the agent brought into that turn. Expand it and click a skill to read the playbook.
- A Skill card appears in the conversation when the agent picks up a skill mid-turn, naming it and linking to it.
- A specialist agent appears under its own name. When the agent hands work to another — “Growth Engineer”, “Data Analyst” — that agent’s steps show under its name, both in the collapsed summary of the turn and in each step as it runs.
- Run details, in the menu that appears when you hover a reply (next to Ask for help), opens the full record of that run: every skill it used and how it reached the run, the memories and definitions it drew on, and the tool evidence behind the answer. The same record is available over the CLI and API.