Conversations

Review what your agents say across every channel, oversee internal AI chats with privacy controls, flag and close conversations, read end-user feedback, and use the dashboard Chat to talk to your own agents.

Every interaction with your agents is logged as a conversation — a web chat, a phone call, a WhatsApp thread, a form-driven exchange, or a member chatting with the AI inside the dashboard. botts.ai gives you two related but distinct surfaces for working with them, plus a built-in Chat for talking to your agents yourself.

Members see only the dashboard Chat. The analytics surfaces are for Builders and above.

Channels

Conversations come from many channels. Each is shown with a colored badge:

Internal chats are a first-class channel with their own privacy and oversight rules — see Internal-chat privacy and oversight.

Why review conversations?

Regularly reviewing conversations is one of the most impactful things you can do to improve your agents:

• Catch errors early — Spot incorrect or incomplete answers before they become patterns.
• Improve your Knowledge Base — If the agent can't answer a question, it usually means the Knowledge Base is missing that information.
• Refine your System Prompt — See whether the agent follows your instructions or drifts off-script.
• Understand your customers — Learn what questions people actually ask, which may differ from what you expected.

The Conversations hub

Open Conversations under the ANALYTICS group in the left sidebar. The hub is a two-pane view: a list of recent conversations on the left and a transcript on the right.

The hub loads the most recent 100 conversations across all channels, ordered newest first. Each row shows:

• A channel badge (Voice, Website, WhatsApp, Telegram, Internal, Email, API, or Chat).
• A caller label — the end user's phone number, or for internal chats the owning member's name or email, otherwise the channel identifier.
• The start time and a message count ("N msgs").
• A flag icon when the conversation has been flagged.
• A rec marker when a voice recording is attached. (The recording itself plays back in the per-agent Chats view, not in the hub.)
• For internal chats, an admin-visibility icon: an emerald lock for private, an amber eye for full. See Internal-chat privacy and oversight.

Click any row to load its transcript in the right pane.

Filtering

The hub has two filters, both applied to the conversations already loaded:

• Channel — Website and the web widget collapse into a single "Website" option; the available options are built from the conversations on screen.
• Source — the deployment the conversation came from.

There is no date-range or end-user search in the hub. To dig into a single agent's history, open that agent's Contacts tab.

Reading a transcript

The transcript shows every message exchanged. For each message you may see:

• The role (the customer/member and the agent).
• Tool-use cards when the agent called a tool — the tool name, its arguments, and its result.
• End-user feedback — a thumbs-up or thumbs-down a customer left on an agent reply, with an optional comment.

Internal chats are not shown in the hub transcript through the analytics path — their content is governed separately (see below).

Flagging and closing

Conversations carry two review states:

• Flagged — a marker (amber flag) you set to revisit a conversation later. Toggle it from an agent's Contacts → Chats view. The hub displays the flag but does not toggle it.
• Status — active or closed. Closing a conversation stamps its end time. When the conversation belongs to an agent, closing it also kicks off a background memory-extraction task, so the agent can carry useful facts forward into future conversations.

Per-agent Contacts and Forms

Open an agent and use its Contacts and Forms tabs to work with that agent's data in detail.

Contacts → Chats

The Contacts tab has two sub-views, toggled at the top: Chats (the default) and People.

The Chats sub-view lists that agent's conversations and adds controls the hub doesn't have:

• A flag toggle.
• A status pill (active / closed).
• A negative-feedback count — a red thumbs-down with the number of replies a customer rated negatively.
• A recording player for voice calls (see Voice recordings).
• The full transcript, including tool-use cards and per-message feedback.

The People sub-view lists the contacts (end users) this agent has interacted with.

Voice recordings

When a voice call has a recording, a player appears above the transcript in Contacts → Chats, streaming the call audio. In the hub, voice rows show only a rec marker — the player itself lives in the per-agent view.

Forms

The Forms tab lists form submissions captured by the agent. It is available to Builder, Admin, and Owner.

• The table is paginated and shows, per submission: the date, the form name, the visitor's name or email (or "Unknown Visitor"), and the first three captured fields (with a "+N more" indicator).
• A search filters by form name.
• Export CSV downloads every submission, with one column per captured field.
• The trash button deletes a submission (after a confirmation). Deleting requires the manage level of forms access.

The dashboard Chat

Chat sits at the top of the left sidebar and is available to every role. It is where you talk to the AI yourself — either with a general-purpose model or with one of your deployed agents. It has two modes.

Agent mode

Agent mode lists agents that have an active internal-chat deployment and that you're allowed to use. Access follows the deployment's setting: open to the whole organization, restricted by minimum role, or invite-only. Each agent shows its title, welcome message, and logo.

A deployed agent runs on the model chosen at deploy time — you can't switch a deployed agent to a different model from the chat. If the primary model fails mid-request, the agent automatically falls back to its configured backup model; the reply records the model that actually answered. (When you chat with an agent you're still building and haven't deployed, it runs as a builder test chat where you can pick the model.)

Regular mode

Regular mode gives you a model picker showing the models your organization is allowed to use, ordered with recommended models first. Each option shows its name, a recommended star, intelligence and speed (each as an "N/5" rating), and hosting country. Text usage is billed in credits.

Model availability is enforced by your organization's data-residency setting: only compliant models appear, and picking a non-compliant one is rejected. If your organization has disabled chat, regular mode is turned off and the model picker is empty.

The regular-mode assistant identifies itself as the built-in assistant of botts.ai (a Swiss agent platform), writes Swiss High German spelling (always "ss", never "ß"), and has no access to your files, emails, or anyone else's conversations — only the current session.

Working in a chat

• Stop generating — while a reply streams, the send button becomes a red stop button; pressing it ends the response cleanly and keeps the text generated so far.
• Voice dictation — the microphone button records you and transcribes the audio into the input box (it is dictation into the text field, not a spoken conversation). Audio is capped at 25 MB.
• Edit and branch — you can edit one of your own messages; this creates a new branch and re-runs the agent's reply. Arrows let you move between branches when a message has more than one version.
• Titles — after your first exchange, a short title is generated automatically. You can rename it.

Endless chat

If your organization has endless chat turned on, the experience changes: new messages continue your existing conversation for the current mode and model/agent instead of starting a fresh one, the conversation sidebar is hidden, and conversations can't be deleted.

Credits

The chat checks your credit balance before sending. If your balance has run out, the send is refused and you'll see an "insufficient credits" notice. Usage is billed in credits.

Internal-chat privacy and oversight

Member-to-AI chats are treated as more sensitive than agent analytics, so they have their own privacy model.

Ownership. Each member's internal chats are private to them. The dashboard Chat lists only your own chats, and no one — not even an Admin or Owner — can edit, delete, or continue another member's chat.

Admin visibility. Your organization has a default policy for internal chats:

Each new chat snapshots the policy in force at the moment it's created. Changing the org policy later only affects new chats — it never retroactively exposes older private chats. The member always sees a badge in the chat header showing the snapshot for the current conversation.

Who can oversee internal chats. Only Owners and Admins get internal-chat oversight. Builders are excluded — in the hub, a Builder never sees other members' internal chats at all (they're filtered out of the list, and opening one returns "not found"). A Builder sees only their own internal chats listed, and even those show no message content in the hub — to read their own internal-chat content, a Builder uses the dashboard Chat.

• Metadata is always visible to Owners and Admins.
• Content is visible only when the caller is the chat's owner, or the caller is an Owner/Admin and that chat's snapshot is full.

When content is withheld, the hub detail pane shows a lock and a "content hidden" notice instead of the messages, and the title is hidden too.

Who sees what

Common patterns to watch for

The improvement loop

The most effective improvement cycle is:

1. Review — Check the latest conversations and the negative-feedback counts.
2. Identify — Find recurring issues or unanswered questions.
3. Fix — Update the Knowledge Base or refine the System Prompt.
4. Test — Use the dashboard Chat in agent mode to verify the fix against the live agent.
5. Monitor — Check follow-up conversations to confirm the improvement.

Over time, this feedback loop makes your agents significantly more accurate and helpful.

Last updated on June 16, 2026