Agent One Teams is a multi-agent AI system that runs customer engagement on behalf of your marketing, ecommerce, and customer engagement teams. You define the outcome, and specialist agents plan, build, launch, analyze, and optimize the work to reach it.
An AI copilot helps with one task, then waits for your next instruction. Agent One Teams works toward the outcome itself, coordinating decisions and execution across the whole customer lifecycle.
Agent One Teams is one of two systems in Agent One. It shares the same live customer profile with Agent One Audiences, so what customers tell your customer-facing agents makes your team's agents smarter.
What Agent One Teams does for you
From one conversational interface, your specialist agents can:
Select the right audiences
Build and orchestrate journeys
Create on-brand content
Coordinate channels and launch experiences
Analyze results and optimize performance
Behind the scenes, three families of specialists work as one team:
Data agents: Unify customer profiles, campaign signals, live intent, and external data, so every decision starts from the fullest context.
Creation agents: Produce on-brand copy, creative, and campaign assets, and adapt content when journeys change.
Journey agents: Plan, build, orchestrate, and optimize journeys across your channels in real time, with no channel-by-channel rebuilds.
Meet your specialist agents
Each agent is built for a specific job. Explore them below.
Agent | What it does for you |
|---|---|
Ask about your marketing performance and customer data in plain language, and get charts and tables you can pin to your own dashboards. No SQL, no waiting on reports. | |
Turns the audience you describe into a ready-to-use segment. | |
Builds campaigns for you, with dedicated agents for SMS, WhatsApp, and email templates: | |
Creates on-brand creative and campaign assets. | |
Plans, builds, and optimizes customer journeys across channels. | |
Answers your questions about Insider One products and features, drawing on Insider One Academy documentation. | |
Adds an AI step to your journeys in Architect. You write the instruction, and for each user it returns an answer you can branch on, personalize messages with, or save to the user profile. | |
Decides the best channel, send time, and content for each customer, and whether to send at all, within the content sets, review steps, and guardrails you define. In Architect, it runs through the Decision Agent element. | |
Connects Insider One to your AI tools through Model Context Protocol (MCP). |
Put agents to work across the lifecycle
Point Agent One Teams at the stage that matters most to you.
Stage | What your agents do |
|---|---|
Acquisition | Identify and convert high-intent customers with coordinated, cross-channel experiences. |
Activation | Guide new customers toward the actions most likely to create value. |
Conversion | Optimize journeys, content, and timing for every customer. |
Retention | Spot changing behavior and act before customers disengage. |
Loyalty | Adapt experiences around customer value, preferences, and long-term intent. |
Re-engagement | Decide when, where, and how to bring customers back. |
Agent One Teams coordinates engagement across email, SMS, WhatsApp, web, mobile app, push notifications, conversational experiences, and emerging AI interfaces. Available channels depend on your implementation and selected Insider One products.
Smarter with every outcome
Every action becomes intelligence for the next one. Agent One Teams measures each outcome, learns from it, and adapts journeys, content, and segments toward your goals.
Its context grows richer over time. The agents learn from customer profiles, campaign performance, channel activity, external data, and the intent customers share through Agent One Audiences. All of it feeds one live customer profile, so results compound instead of resetting with every campaign.
You stay in control
Agent One Teams doesn't replace marketers. Your team owns the strategy, brand standards, guardrails, and level of autonomy, and hands over only the planning, decisions, execution, and optimization it chooses.
Choose an autonomy level for each use case, from Command Mode to Autonomous Mode. For a side-by-side view of all four modes, see Agent One.