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  • AI Agent Configuration (timezone, format, options)
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Documentation / AI Agents / AI Agent Configuration (timezone, format, options)

AI Agent Configuration (timezone, format, options)

ES EN

The AI Agent has several configuration options grouped in the edit panel (Management → AI Agents → Edit). This guide covers the most important ones, starting with regional configuration (timezone and date format) which directly affects how the agent responds about dates and times.

Looking for prompt variables? This guide covers where to configure the agent. To learn how to use variables ({{current_time_local}}, {{today_formatted_local}}, etc.) in your prompt, go to Prompt variables.

🌍 Regional configuration (timezone and date format)

Each AI Agent has two selectors that define how it understands and communicates time:

SelectorWhat it controlsExample
Timezone The real time reference for all calculations Europe/Madrid (+02:00)
Date format How dates are written when spoken es_ES → viernes, 17 de abril de 2026

You'll find them in Basic Configuration when editing the agent:

Basic Configuration
├── Agent Name
├── Timezone        ← here
├── Date format     ← here
└── Description

🏢 Hierarchy: organization, workspace, agent

MuseRelay has a hierarchical structure:

Organization
├── Workspace 1
│   ├── Agent A
│   └── Agent B
└── Workspace 2
    └── Agent C

Regional configuration lives at two levels:

  1. Organization level (all agents inherit by default) — set under Settings → Organization.
  2. Agent level (optional override) — the agent can have its own timezone/format that overrides the organization.

Resolution cascade

For each agent, the system resolves the configuration in this order:

  1. Does the agent have an explicit value? → use that.
  2. If set to "Inherit" → does the organization have a value? → use the organization's.
  3. If both are empty → fallback:
    • Timezone → UTC.
    • Date format → en_US.

Practical example

A retail chain with organization "Screen Art" configured as Europe/Madrid + es_ES:

WorkspaceAgentAgent configResult
Madrid Store Agent A Inherit Madrid · es_ES ✅
Barcelona Store Agent B Inherit Madrid · es_ES ✅
Madrid Store Agent C Override: America/Mexico_City + es_MX Mexico City · es_MX ✅ (override wins)

🕐 What changes with the timezone

The agent's timezone affects all _local variables in the prompt and the auto-injected context block. Example with the same real time (April 17, 2026, 15:47 UTC):

🇪🇸 Europe/Madrid + es_ES

{{current_time_local}} → 17:47
{{today_formatted_local}} → viernes, 17 de abril de 2026

🇲🇽 America/Mexico_City + es_MX

{{current_time_local}} → 09:47
{{today_formatted_local}} → viernes, 17 de abril de 2026

🇯🇵 Asia/Tokyo + ja_JP

{{current_time_local}} → 00:47 (day 18)
{{today_formatted_local}} → 2026年4月18日土曜日

📦 Auto-injected context block

Regardless of whether you use variables in your prompt, the system always prepends to the start of your agent's prompt this block before sending it to the model:

## Current context (injected by the system, do not modify)
- Current time: 15:47 (Europe/Madrid)
- Date: Friday, April 17, 2026
- Tomorrow: Saturday, April 18, 2026
- Agent timezone: Europe/Madrid
- Format locale: es_ES

This ensures the agent always knows the real date and time, without depending on you remembering to use variables.

💡 Recommendations

  • By default, leave the agent selectors as "Inherit" and configure the zone at the organization level. This way all agents use the same configuration and you only change one place.
  • Override only when needed: if the same organization serves multiple countries, create agents with per-zone overrides (one agent per country).
  • For international audiences where customer time matters, consider creating one organization per country — the cleanest pattern in multi-tenant.
  • Hot changes: if you edit the timezone of the agent or the organization, the model sees the new values in the next conversation. No restart needed.

🛠️ Other agent configuration options

Besides the regional config, the agent edit panel has:

  • Name and description — what your agent is called and what it does.
  • Prompt configuration — the system prompt that defines the behavior. See Prompt variables.
  • Custom variables — your own variables in JSON (e.g. {{company}}, {{store_hours}}).
  • Calendar Commands (Cal.com) — so the agent can book appointments. Requires API key + Event Type ID.
  • Advanced configuration — streaming, max tokens, creativity (temperature).

Each one is documented separately in this section.

Frequently asked questions

What's the difference between timezone and date format?
Timezone controls when (at what real time "today", "tomorrow", "now" are calculated). Date format controls how it's written when telling it to the customer. You can have Madrid as zone but English as format (rare but possible) — the agent reasons in Madrid time but communicates in English.
If I change the organization's timezone, does it affect existing agents?
Yes — agents set to "Inherit" start using the new zone on their next conversation. Agents with their own override don't change.
Can I have agents in different timezones within the same organization?
Yes. Configure the organization with the most common zone and set overrides only on agents that serve other zones. For example: organization Europe/Madrid, and a specific agent with America/Mexico_City for Mexican customers.
Does it work with daylight saving time?
Yes. IANA timezones (Europe/Madrid, America/New_York, etc.) automatically include DST. In winter Madrid is +01:00 and in summer +02:00 — the system adjusts automatically.
What if I leave everything as "Inherit" and the organization is also empty?
Falls back to UTC + en_US. It works but dates are shown in English and the time may not match your customer's zone. It's best to at least configure the organization.

🕐 Who sees what time? Embed chatbot vs agent panel

A common question: who exactly is affected by the regional settings of the agent? The answer matters because the AI agent and the humans viewing conversations may be in different timezones.

Two interfaces, two different rules

ViewWho reads itTimezone shown
Embed chatbot
(widget on the customer's website)
End customer (website visitor) Visitor's browser timezone (auto)
Agent panel
(/agent/conversation/{id})
Human operator of MuseRelay AI agent's configured timezone

Why the embed chatbot uses the browser's timezone

If a Mexico City customer reads the chat on their web:

  • Their clock shows 09:15.
  • If the bot shows "I'll reply at 09:15" → matches their clock ✅.
  • If it showed "I'll reply at 16:15" (Madrid time) → confusion ❌.

It's what WhatsApp, Messenger, Telegram, Slack do: everyone sees the time in their own zone. Zero configuration, zero confusion for the end customer.

Why the agent panel uses the agent/operator's timezone

The MuseRelay human operator is working and needs to see times in their work zone. If they handle support from Madrid but a Mexican customer wrote at 02:15 CDMX (09:15 Madrid), the operator wants to see "09:15 Madrid" to know when to reply.

In the internal panel the system uses this cascade:

  1. Operator user's timezone (if set).
  2. Organization's timezone.
  3. Fallback to Europe/Madrid.

Modern chat-style day separators

The embed chatbot groups messages by day using the visitor's browser timezone, like WhatsApp or Telegram:

─────── Today ───────
14:30  Message 1
14:32  Message 2

─────── Yesterday ───────
09:15  Message 3

─── Wednesday, April 15 ───
11:00  Message 4

─── March 2, 2026 ───
Older message

Separator rules:

  • "Today" → messages of the visitor's current day.
  • "Yesterday" → previous day.
  • Weekday + date → last 7 days.
  • Full date → older.

Each individual message shows only the time (14:30). The separator already says what day, so it doesn't repeat.

Visual summary

General rule:
  • 🌐 End customer reads on their website → browser time.
  • 👨‍💼 Your team reads in the MuseRelay panel → agent configured time.
  • 🤖 AI agent reasons internally → agent configured time (for "today", "tomorrow", schedules).

Each side sees the useful time without stepping on the others.

Siguiente →AI Agent prompt variables
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