AI Agent & Conversational UX Design Services

Show the draft as it will be sent, with the recipient, the channel and the context the assistant used — the deal, the last email, the note it drew on. The rep can edit, approve or reject, and nothing leaves until they do. Approval can relax for low-risk messages once people trust the assistant, but not silently. Where the channel allows, a short delay gives a way to undo, and every sent message stays in the history with who approved it.

Ask for an agent designed end to end, not a chat screen: the setup, the permission model, the preview before an action, the approval, and what happens when the agent is stopped, blocked or wrong. Ask how the team mapped every branch before drawing UI, and whether the work was a live product. Our Nexus case shows that range for an agent builder and browser tasks people can watch and take over.

The people who configure agents and set their limits, the people who hand them tasks and approve their work, admins who manage access and credentials, and the customers or colleagues on the other side of an action. The workflows are setup by conversation, briefing a task, reviewing drafts and previews, approving or rejecting, following an agent at work, and stopping, undoing or retrying. Conversational AI design covers the dialogue itself: how the agent asks back, confirms and admits it is unsure.

Product Discovery if you are still choosing the job to hand the agent, and a UX Audit if a live assistant confuses people. UI/UX & Product Design covers a new agent from setup and permissions to the stop button; Web App Design and Mobile App Design cover the surfaces people use it on. When the product is broader than one agent — predictions, recommendations, generated content — AI Product Design is the wider frame. CRM Development builds an assistant into a sales team's CRM.

Permissions come first: which tools, data, accounts and spend the agent may use, per role and per task, set out in a matrix engineering can check the build against. Then every screen is drawn for the agent working, a draft waiting for review, an approval pending, an action blocked by a permission, a request for sign-in or payment, a question back to the user, an unavailable tool, a stop, and a finished task with each step logged.

Access to the current build or prototype, the tasks the agent should take on, and the tools and data it can reach. A product owner who can decide where people must approve, and time with the engineers behind the model and orchestration, so the design shows only what the system can actually report.

Nexus, agentic AI for company teams: we designed an Agent Builder set up through chat, Computer Use for browser tasks people can watch and take over, and the Vault for the data those tasks may use — 200+ unique screens, with 3 experts on the team. Moka, an AI academic assistant, where we designed the student chat — conversational help a stressed student can trust; the platform around it came to 200+ screens designed by 4 experts, and a 5.0★ client rating.

Yes. Agents rarely arrive in a new product; they join one people already use. Your designers and the engineers building the agent see every step in your own files, and each flow is drawn around what your stack can expose. On Nexus we handed engineering the flows, a prototype and a design system; the build was not ours.