AI Agents
Dynaris is built on a multi-agent architecture in which specialized AI agents work together to complete tasks. Instead of relying on a single general-purpose assistant, Dynaris uses a coordinated team of agents, each designed for a specific type of work and equipped with the tools needed to perform it well.
This structure allows Dynaris to handle more complex requests with greater accuracy, better task delegation, and clearer execution across your connected tools and data.
How AI Agents Work
When you send a request, Dynaris begins by passing it to a central Supervisor Agent. The Supervisor interprets your goal, determines what needs to be done, and creates an execution plan.
If the request involves multiple steps, the Supervisor assigns each part of the task to the most appropriate specialized agent. Each agent completes its portion of the work, and the Supervisor combines the outputs into a single, structured response.
For example, a single request might involve retrieving lead data, drafting an email, scheduling a follow-up, and updating records. Rather than handling everything through one generic process, Dynaris distributes the work to agents designed for each domain.
Why This Architecture Matters
The multi-agent model improves both execution quality and scalability.
Because each agent is focused on a specific domain, Dynaris can:
- Perform tasks with more precision
- Use the correct tools for each job
- Coordinate multi-step workflows more effectively
- Deliver clearer and more reliable results
This makes Dynaris especially effective for operational workflows that span communication, scheduling, research, lead management, documents, and automation.
Built-In Agents
Dynaris includes a set of built-in agents that are available as part of the platform.
| Agent | What it does |
|---|---|
| Gmail Agent | Sends emails, searches inboxes, manages drafts, labels, and threads |
| Outbound Agent | Manages outreach across email, voice, SMS, and WhatsApp |
| Scheduler Agent | Creates and manages scheduled workflows using one-time, recurring, or rate-based triggers |
| Web Research Agent | Searches the web, crawls pages, and extracts structured information |
| Data Analysis Agent | Analyzes datasets using natural language queries and exports results |
| Document Agent | Creates documents, searches uploaded knowledge, and manages reports |
| Contacts Agent | Creates, updates, and searches lead and contact records |
| Composio Agent | Manages connected app actions and OAuth-based integrations across supported tools |
| Voice Agent | Handles AI-powered inbound and outbound phone interactions |
| Workflow Architect | Designs custom agents and workflow structures based on your requirements |
Creating Custom Agents
In addition to the built-in agents, Dynaris allows you to create custom agents tailored to your own workflows.
Custom agents are created through the Workflow Architect. You describe what the agent should do, which tools it should use, and how it should behave. Dynaris then generates an agent configured for that purpose.
Custom agents can be used across conversations and can work alongside built-in agents as part of larger workflows.
A request such as:
"Create an agent that monitors my GitHub repositories for new issues and posts a summary to Slack every morning"
can be turned into a reusable agent that becomes part of your Dynaris environment.
How Agents Collaborate
One of the main strengths of Dynaris is agent collaboration. A single request can trigger several agents working together in sequence.
For example, Dynaris might:
- Use the Web Research Agent to identify companies
- Use the Contacts Agent to save them as leads
- Use the Gmail Agent to draft outreach messages
- Use the Scheduler Agent to create follow-up tasks
Although multiple agents may be involved, the entire workflow is handled inside one conversation and returned as a single coordinated result.
Visibility Into Agent Activity
Dynaris is designed to make agent activity understandable and reviewable.
As agents work, you can see:
- Which agent is handling each task
- Which tools are being used
- The outputs returned by those tools
- Progress as the request moves through each step
This gives you visibility into how Dynaris is executing your request and helps you understand what actions are being taken on your behalf.
What This Means for You
With AI agents, Dynaris is not limited to answering prompts. It can interpret goals, break them into steps, assign the right execution path, and complete operational work across your systems.
This allows you to move from simple requests to complete workflows without manually switching between tools or coordinating separate actions yourself.
What's Next
Once you understand how agents work, the next step is to see how they operate with your integrations, workflows, and automations.
Continue to the next section to learn how Dynaris uses connected tools and events to turn agent decisions into real actions.