This guide explains how to migrate from legacy MagicReply chatbots to Hugo AI Agent while keeping the useful parts of your existing setup.

Hugo AI Agent replaces the legacy MagicReply approach with a more configurable AI setup. Knowledge, behavioral instructions, routing, workflows, integrations, testing, and monitoring now have dedicated sections instead of being combined inside workflow branches and prompts.

Your existing Workflows remain available while you prepare and test Hugo, so you can migrate progressively before switching your live conversations.

Hugo uses AI credits, but credits are included with paid plans and you can configure workspace and per-conversation spending limits. Jump to how to keep Hugo AI costs under control if cost is your main concern.

This guide is split into practical sections:

• Why move from MagicReply to Hugo → understand the main differences between both AI setups
• Watch the migration walkthrough → see the migration flow in video format
• Map your MagicReply setup to Hugo → understand where your existing configuration belongs
• Adapt your System Prompt and Workflows to Hugo → understand the two main changes in the migration
• Migrate your MagicReply setup → move each part to the appropriate Hugo feature
• Keep Hugo AI costs under control → configure credits, Pay-As-You-Go, and spending limits
• Test Hugo before going live → validate your migrated setup safely
• Activate Hugo → switch live conversations to Hugo

Why moving from MagicReply to Hugo

MagicReply added AI-generated answers inside Workflows. Hugo turns AI into a dedicated agent that can use several configuration layers together when handling a customer conversation.

The main difference is that knowledge, behavior, routing, models, integrations, and monitoring can now be configured independently.

Hugo can combine these settings with the current conversation context when preparing an answer. This gives you more control over how answers are generated and lets you update one part of the AI setup without rebuilding the entire automation.

For a complete overview, read how to navigate the Hugo AI Agent interface and features.

Watch the migration walkthrough

This video shows the main differences between MagicReply and Hugo and how to reorganize an existing chatbot setup.

Map your MagicReply setup to Hugo

MagicReply concentrated much of the AI configuration inside Workflows and the System Prompt.

Hugo separates these responsibilities into dedicated areas for knowledge, behavior, routing, automation, integrations, testing, and monitoring.

The main Hugo sections are:

1. Train → give Hugo the information it needs to answer customers
2. Instructions → define how Hugo should behave and communicate
3. Routing → decide what Hugo should do when specific situations occur
4. Workflow Builder → keep structured processes and deterministic automations
5. Settings → configure models, escalation, behavior, and conversation limits
6. Integrations & MCP → connect Hugo to external data and actions
7. Playground → test Hugo before using it with customers
8. Analytics & Observability → monitor performance and inspect real conversations

Use this mapping when reviewing your existing MagicReply configuration:

Adapt your System Prompt and Workflows to Hugo

The System Prompt and Workflows are the two parts of a MagicReply setup that require the biggest change in approach.

Move your MagicReply System Prompt

The MagicReply System Prompt could contain several types of information in the same field, including tone, behavioral instructions, product facts, business context, and rules for specific situations.

With Hugo, these elements should be separated.

Move each part of your System Prompt to the appropriate Hugo section:

• Behavior, tone, boundaries, and response rules → AI Agent → Guidance → Instructions
• Product facts, policies, documentation, and business information → AI Agent → Train
• Situations that should trigger an action → AI Agent → Guidance → Routing

For example:

Always keep answers short and professional belongs in Instructions.

Refunds are available for 30 days after purchase belongs in Train.

Read how to write Hugo Instructions for AI Agent and Copilot and how to train Hugo AI Agent on your data before moving your System Prompt.

Adapt your Workflows

Workflows remain available with Hugo, but they no longer need to contain the full AI conversation logic.

Keep Workflows for structured processes where specific steps or actions should happen in a predictable order.

Typical Workflow use cases include:

• Collecting required information
• Showing buttons or choices
• Checking conditions
• Updating conversation or customer data
• Triggering internal actions
• Guiding users through a fixed sequence

Hugo and Workflows can work together in both directions.

Hugo can start a Workflow when a Routing rule detects a situation that requires a structured process.

For example, Hugo can handle regular support questions and start a refund Workflow only when the customer asks for a refund.

Read how to start Workflows situationally with Hugo AI Routing.

A Workflow can also hand the conversation to Hugo with the Answer with Hugo block.

When this block is reached, the Workflow ends and Hugo continues the conversation. Context collected during the Workflow can be passed to Hugo for the handoff.

Read how to start Hugo from a Workflow.

For the full Workflow Builder setup, read Getting started with Crisp Workflows.

Migrate your MagicReply setup

Once you understand where each part belongs, review your current MagicReply configuration and migrate it section by section.

Audit your existing setup

Open your current Workflows and review your MagicReply blocks, System Prompt, branches, and fallback logic.

Identify which elements are:

• Knowledge → information Hugo needs to know
• Behavior → rules Hugo should follow
• Decisions → situations that should trigger an action
• Processes → structured steps that should remain as Workflows

This gives you a clear list of what needs to move and what can stay.

Move your knowledge to Train

Add factual information under AI Agent → Train.

Depending on your content, you can use Questions & Answers, web pages, files, or your Crisp Knowledge Base.

Avoid keeping important support information inside old Workflow branches when Hugo should be able to use it across conversations.

Read how to train Hugo AI Agent on your data.

Move conversation decisions to Routing

Use AI Agent → Guidance → Routing for decisions that depend on what the customer is asking or what is happening in the conversation.

A Routing rule can start a Workflow, move a conversation to another inbox, escalate the conversation, or decide when Hugo should handle a situation.

Read how Hugo AI Agent Routing works.

Connect live data through Integrations & MCP

Training resources are designed for information Hugo can learn and retrieve later.

If an answer depends on live information such as an order, subscription, account status, or another external value, use AI Agent → Automate → Integrations & MCP instead.

Read how to use Hugo Integrations for supported integrations, or how to build MCP integrations with Hugo to connect your own systems.

Once these elements are migrated, review the System Prompt and Workflow changes described in the previous section before moving to testing.

Keep Hugo AI costs under control

Hugo uses AI credits when the AI Agent is involved in a conversation.

Monthly AI credits are already included with paid Crisp plans. You can monitor the remaining balance and usage from AI Agent → Agent → Billing.

If the included credits are exhausted, Hugo does not create unlimited additional charges by default. Conversations can instead be escalated to human operators.

You can optionally enable Pay-As-You-Go if you want Hugo to continue handling conversations after the included credits are exhausted.

Set a Pay-As-You-Go limit

Pay-As-You-Go can have its own maximum spending limit.

Go to AI Agent → Agent → Billing and click Edit limit under Pay-As-You-Go.

This gives you a workspace-level ceiling for additional AI usage beyond your included credits.

Limit spending per conversation

You can also define how much Hugo is allowed to spend inside one conversation.

Go to AI Agent → Agent → Settings, enable Limit AI spend per conversation, then enter the maximum amount.

When the conversation budget is reached, Hugo escalates the conversation instead of continuing to consume AI credits.

You can therefore control AI spending at two levels:

• Pay-As-You-Go limit → limits additional AI spending across the workspace
• Conversation budget → limits spending inside an individual conversation

Workflows themselves remain free and do not consume Hugo credits. Credits are used when Hugo or another AI-powered action is involved.

For complete billing rules and usage details, read how Hugo AI pricing and billing work.

Test Hugo before going live

Once your MagicReply configuration has been migrated, go to AI Agent → Evaluate → Playground.

The Playground lets you test the current Hugo setup without activating the AI Agent for live customer conversations.

Use real support questions and check that Hugo:

1. Finds the correct information
2. Follows your Instructions
3. Triggers the expected Routing rules and Workflows
4. Escalates when it should not answer
5. Handles follow-up questions correctly

You can also compare AI models from the Playground to review their answers before choosing the model used by Hugo.

Read how to choose and configure Hugo's AI model.

For conversations already handled by Hugo, use Hugo Observability to monitor and debug AI Agent conversations.

Activate Hugo

When your tests are reliable, open AI Agent → Agent → Activation.

Enable Hugo for new conversations and configure where and when the AI Agent should handle customer requests.

From the Activation settings, you can control:

• Which conversation channels Hugo handles
• The default destination for incoming conversations
• How conversations are escalated to your team
• When Hugo is active based on your configuration

Your migrated Workflows remain available and can continue running through Hugo Routing or their other supported activation methods.

For the complete activation process, read Getting started with Hugo AI Agent.

Updated on: 26/08/2026