Moving on from product updates, Sandra chooses to review all agent builds, deployed and in progress, along with the current in-focus agent: “Cora Support - Chat.”

This is where Zeon's deployments live. Every agent across every channel: chat, voice, email, and more. All built, configured, and managed from the same platform.

Zeon is chat-first today but is preparing to deploy multi-channel support soon, and her team is already building those solutions. The full picture is visible right here, and the infrastructure to expand is in place.

After reviewing the AI agent builds, Sandra moves to review the Assigned Users tab.

Her full team is here. Roles, permissions, and section-level access, all configurable from one place. She can see who has access to what, make changes directly, and trigger a historical audit of any user's activity, opening the Activity Log filtered to that user.

Agentic Studio has evolved from a flat org to a dynamic one, with role variability that fits every job. This allowed Sandra to grow from an army of one to bringing on specialized talent for dedicated tasks.

Sandra moves to the Activity Log tab.

Beyond seeing all historical actions taken by her team, a feature just recently introduced to the Account section, Sandra as admin has the final say in rolling back changes to workflows, personas, actions, and more. Management is no longer reactive, but proactive.

Sandra's team has been crafting new capabilities for their chat-based AI agent, to better shape AI response behaviour.

The AI Persona section, under the Prompt Manager, is where this work starts. As Netomi expanded to support third-party LLMs, they introduced an exposed tuning layer, giving customers a way to define the agent's voice, tone, and personality. Sandra has that now. A consistent, configurable identity, regardless of which model runs underneath. Once built, the Evaluation tab lets her test and measure performance.

With the AI Persona reviewed, Sandra turns to the equally new Actions section, under Training, here to check in on the recent agentic enhancements made to Zeon's existing deployment by her team.

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From looking up order status to triggering a return, Actions are the operational layer of the agent and the foundation of agentic behaviour. Rather than just responding, the agent acts: completing processes, moving data, resolving issues end-to-end without human intervention.

Pete Fergus is outfitting a new commercial office space. He generally knows what he needs: smart lighting, IoT-ready, something that scales. But he wants to browse and buy while getting his technical questions answered at the same time.

So far, calls to other suppliers haven't delivered. No one could cohesively answer his questions alongside the buying process. He's turned to searching online, manually working through site after site. There has to be a better way.

Pete is frustrated. The process has been anything but simple. With Netomi's Conversational AI, it's possible.

Pete is exploring Zeon's website and products when he spots the chat widget.

He engages with Cora, Zeon's chat-based AI agent, about a specific fixture: compatibility with his existing IoT setup, availability, lead time. Through every turn of the conversation, Cora stays on track, confirming the fixture works with his current setup, checking stock, flagging lead time, then pulling the matching products together so he can act right there. Fast. Accurate. Exactly on-brand. The technical answer and the buying path, in one conversation.

Later that week, Sandra opens Conversation Viewer to review how her AI agent performed across recent customer interactions.

She finds Pete's session and reads through it. Sentiment markers. Satisfaction signals. Keyword patterns. How the agent handled each technical question. None of this existed before. Reviewing a conversation meant reading a raw transcript and inferring the rest. Now the signals sit at the surface, and patterns needing a wider view link straight to the quantitative dashboards. Sandra sees the story, not just the transcript.

Wanting a larger, more quantitative perspective, Sandra moves to the redesigned Overview Dashboard, where the monthly numbers tell a strong story overall.

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Resolution rate up. Response times down. Satisfaction holding above target. But Sandra looks closer. There's a pattern. A cluster of questions triggering handoffs, driven by complexity or gaps in the knowledge base. From here, she can take action to close those gaps, retrain, retest, and relaunch, widening what the agent resolves on its own.

Even with the best-built AI system, comprising a strong knowledge base, solid processes and guardrails, and an advanced LLM at the helm, AI agents have their limits. Some situations call for a human touch: a complex complaint, an unusual request, something automation simply can't resolve. This is where a live agent handoff comes in.

When that moment arrives, Agentic Studio escalates cleanly to a live agent working via AgentDesk, carrying the full conversation history with it. For the customer, it feels seamless. For the agent receiving it, they're already up to speed. How?...

Back to Sandra, Cora, and Pete...

Agentic Studio manages every step of the conversational lifecycle. Sandra and her team configure Cora, the AI agent, to perfectly answer queries and take action as needed. In the rare event an end-customer like Pete needs a human touch, Netomi covers that handoff seamlessly, as reflected above.

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Sandra and her team turn qualitative and quantitative data into continuous, targeted experience tweaks. By constantly pushing AI success metrics higher, they build a reliable ecosystem Zeon’s customers can trust.