Agent to Agent Connection

Most AI systems operate in isolation — like machines working alone on separate assembly lines.
GTWY rewrites that architecture.

Agent to Agent Connection allows two or more AI agents to communicate, share context, and execute tasks together — without you manually coordinating anything.

Agents can now hand off information, extend each other’s work, and enhance outputs using shared intelligence.

Your GTWY workspace becomes a network of collaborating AI systems instead of individual bots.
This is how true automation should function: connected, autonomous, and self-coordinating.

Modern workflows are rarely handled by a single AI. Different tasks require specialized expertise:

• A data extraction agent pulls information

• A summarization agent condenses it

• A response agent formats the final output

Without coordination, you’d manually shuttle data between them.

GTWY eliminates that.
The agents talk to each other directly.

• Faster execution: Real-time data transfer between agents

• Smarter cooperation: Every agent stays focused on its specialty

• Consistent results: Shared context = zero loss of information

• Scalable automation: Chain multiple agents to handle highly complex processes

This is multi-agent intelligence — not the future, but the present.

Connecting agents is simple, deliberate, and engineered for performance.

Among the panel section open connection, move to the agents section and click on add agents.

You’ll see a list of all published and unpublished agents in your organization, select the agent you’ve published.

Select the agent you want to connect and open its configuration panel.

Inside the Agent Config, you can define important details about the connected agent. The configuration panel allows you to manage how agents communicate and what information is shared during execution.

You can configure the following:

• Agent’s Version – Choose which version of the agent should be used. Typically this will be the Published Version, ensuring the workflow uses the stable version of the agent.

• Name & Description – Define a clear name and description so you can easily identify the purpose of the connected agent and how it differs from others.

• Agent’s Thread ID (Optional) – This can be enabled when you want the agent to operate within a specific conversation thread.

These settings help maintain clarity and control when multiple agents are connected in a workflow.

The Parameters section allows you to define what information will be passed to the connected agent.

You can create parameters that control how the receiving agent behaves. Each parameter can be configured with several options:

• Required – Ensures that the parameter must be provided before the agent executes.

• Fill with AI – Allows the system to automatically generate the parameter value using AI if needed.

• Type Selection – Define the parameter type (for example, String).

• Allowed Values – Restrict the parameter to specific predefined values when necessary.

• Value Path – Define the path from where the parameter value should be extracted.

These parameters allow agents to exchange structured information, ensuring consistent communication between them.

Write rules or conditions that determine when and how the connected agent should be invoked.

After configuring the agent:

1. Select the agent you want to connect.

2. Configure the version, name, description, and parameters.

3. Test the setup to confirm that the agents communicate correctly.

Once validated, deploy the workflow. The agents will now collaborate automatically.

• Agent A collects queries

• Agent B drafts responses

• Agent C adjusts tone and finalizes the reply
  All connected. Zero manual effort.

• Research agent → Writing agent → Editing agent
  A full content assembly line powered entirely by AI.

• Data retrieval agent

• Insights summarization agent

• Visualization agent
  Together, they produce complete analytical outputs.

Agent networks turn linear tasks into autonomous, coordinated operations.

Agent to Agent Connection transforms GTWY from an AI platform into a multi-agent ecosystem.

Instead of isolated tools, you now orchestrate a synchronized network of intelligent systems — each agent contributing its expertise toward one unified outcome.

Whether you’re automating support, generating content, or processing data at scale, connected agents work faster, think smarter, and operate more efficiently than any standalone model.

Work smarter, not harder.
Let your agents collaborate — and let GTWY make the system intelligent. 🚀