Skip to main content

​
Deployments

Deployments are how you make your AI configuration available to users. Think of them as versioned releases - each deployment is an immutable snapshot of your AI’s complete configuration at a specific point in time. Understanding how deployments work ensures smooth, controlled updates without disrupting live customer interactions.

​
Why Deployments Matter

Deployments enable:
  • Safe updates - Test changes before going live
  • Version control - Track what changed and when
  • Easy rollback - Revert to previous versions if needed
  • Consistency - All channels use the same version simultaneously
  • Audit trail - See complete history of your AI’s evolution
Deployments separate development from production. You can continue refining your AI while users interact with a stable, tested version.

​
How Deployments Work

The deployment system has three key concepts:

​
1. Versions (Deployments)

Versions are numbered snapshots (#1, #2, #3…) containing:
  • Profile configuration (guidance, tools, LLM settings)
  • Knowledge snapshots (all sources at build time)
  • Creation timestamp
  • Immutable - never changes after creation
Creation: Building a profile version creates a new deployment automatically. Numbering: Sequential numbers (#1, #2, #3) assigned automatically as you build versions.

​
2. Production Alias

Production Alias is a pointer to a specific deployment version:
  • Represents “currently active” configuration
  • Can be updated to point to different versions
  • All channels connected to this alias use its current version
  • Usually named “Production” or similar
Purpose: Allows switching versions without reconfiguring channels.

​
3. Channels

Channels are where users interact with your AI:
  • Website widgets (Frames)
  • Zendesk integration
  • Salesforce integration
  • Slack integration
  • WhatsApp integration
Connection: Channels connect to the Production Alias, not directly to versions. When you update the alias, all connected channels automatically use the new version.

​
Deployment Architecture

Website Widget ─┐
Zendesk        ─┼─→ Production Alias ─→ Version #5 (Profile v0.5)
Salesforce     ─┤                          ├─ Knowledge Snapshot
Slack          ─┘                          ├─ Guidance Rules
                                           ├─ Tool Configuration
                                           └─ LLM Settings

Available Versions:
├─ Version #5 (active) ← Production points here
├─ Version #4
├─ Version #3
├─ Version #2
└─ Version #1

​
Building and Deploying

The typical workflow for deploying AI changes:

​
Step 1: Make Changes

Edit your AI configuration:
  • Update guidance instructions
  • Add knowledge sources
  • Enable/disable tools
  • Adjust audiences
Changes are not immediately deployed - they’re saved in your editing session.

​
Step 2: Build Version

Navigate to Behavior → [Review your changes] and click Build Version, Set Active This process:
  1. Creates new profile (e.g., v0.5 → v0.6)
  2. Captures knowledge snapshot - Indexes current state of all data providers
  3. Builds deployment - Compiles everything into deployable package
  4. Updates Production Alias - Points to new version
  5. Deploys to all channels - All connected integrations use new version
Build time: 30-60 seconds for most configurations
Building creates an immutable deployment. Once built, versions cannot be modified - you must build a new version for any changes.

​
Step 3: Monitor Impact

After deployment:
  1. Check conversations for new version
  2. Monitor metrics (CSAT, resolution rate)
  3. Review for any issues
  4. Rollback if needed (see below)

​
Build Options Explained

Build Version, Set Active (Recommended)
  • Creates deployment AND sets as production
  • All channels immediately use new version
  • Takes 30-60 seconds
  • Use for: Normal updates
Build Version (Advanced)
  • Creates deployment without setting as production
  • Test version before going live
  • Manually set as active later
  • Use for: Major changes you want to review first
Build Version, Set Active, Get Email (Enterprise)
  • For deployments affecting many channels
  • Runs asynchronously in background
  • Email notification when complete
  • Use for: Large-scale deployments with 10+ channels

​
Managing Versions

View and manage all versions in Behavior → General → Versions

​
Version List

Each version shows:
  • Version number (#1, #2, #3…)
  • Profile name (v0.0, v0.1, v0.2…)
  • Status - “Production” badge if active
  • Creation date - When version was built
  • Description - Build notes (e.g., “Build for profile v0.5”)

​
Setting a Version as Active

To switch production to a different version:
  1. Navigate to Behavior → General
  2. Find the version you want to activate
  3. Click the ⋮ menu next to the version
  4. Select Set as Active
  5. Confirm the change
What happens:
  • Production Alias updates to new version
  • All channels switch immediately
  • Previous version remains available for rollback
Changing active version affects all connected channels immediately. Users will see the new version in their next interaction.

​
Rolling Back

If a deployment causes issues, roll back quickly:

​
Quick Rollback Process

  1. Identify the problem - Check conversations, metrics, errors
  2. Navigate to Versions - Behavior → General → Versions
  3. Find previous good version - Usually the version before current
  4. Set as Active - Click ⋮ → Set as Active
  5. Verify - Test with sample questions
  6. Investigate - Determine what went wrong

​
When to Roll Back

Immediate rollback if:
  • CSAT drops significantly (> 0.5 points)
  • High error rates in conversations
  • Knowledge sources missing or incorrect
  • Tools not working as expected
  • User complaints spike
Wait and monitor if:
  • Minor changes in metrics
  • Isolated issues affecting few users
  • Issues can be fixed quickly with knowledge updates

​
Post-Rollback

After rolling back:
  1. Review what changed between versions
  2. Identify root cause
  3. Fix in development
  4. Test thoroughly
  5. Build and deploy again when ready

​
Channels and Production Alias

Understanding how channels connect to deployments helps manage updates effectively.

​
Viewing Connected Channels

Navigate to Behavior → General → Channels to see:
  • All active channels
  • Which alias they’re connected to
  • Current version each is using
  • Links to configure each channel

​
Channel Display

For each channel, you’ll see: 
[Website Widget] ─→ [Production Alias] ─→ [Version #5]
  My Website                                  v0.5
                                              2 days ago

​
Adding Channels

Channels are configured outside the Behavior section:
  • Website Widgets: Navigate to Frames
  • Zendesk: Navigate to Integrations → Zendesk
  • Salesforce: Navigate to Integrations → Salesforce
  • Slack: Navigate to Integrations → Slack
  • WhatsApp: Navigate to Integrations → WhatsApp
Once configured, channels automatically appear in Behavior → General → Channels.

​
Knowledge Snapshots

Each deployment includes a knowledge snapshot capturing all sources at build time.

​
What’s Included

When you build a version, the knowledge snapshot includes:
  • All synced data provider sources
  • All snippets from collections
  • Search table data (references, not copies)
  • Current state of all embeddings

​
Knowledge Staleness Indicator

After data providers sync new content, you’ll see:
  • Orange indicator: “Knowledge sources updated, rebuild needed”
  • Rebuild to update: Build new version to incorporate latest knowledge
  • Automatic syncs: If you have scheduled syncs, periodic rebuilds keep knowledge current
Schedule regular builds (weekly or monthly) if you have frequently updating data providers. This ensures your AI always has the latest knowledge.

​
Best Practices

​
Version Management

Build frequently for active development
  • During initial setup: Build after each significant change
  • Test each version before setting as production
  • Keep version history clean
Build less frequently for stable deployments
  • Weekly or monthly builds to incorporate knowledge updates
  • Only build for actual improvements, not minor tweaks
  • Batch multiple small changes into one version

​
Naming and Documentation

Profile names (v0.0, v0.1, v0.2):
  • Increment minor version for small changes (v0.5 → v0.6)
  • Increment major version for significant changes (v0.9 → v1.0)
  • Major version = new features, major guidance changes
  • Minor version = refinements, knowledge updates
Tracking changes: Keep notes of what changed in each version: 
v0.6: Added 15 snippets for API questions, updated tone guidance
v0.5: Enabled search_web tool, reorganized guidance priority
v0.4: Fixed billing knowledge gaps, improved escalation criteria

​
Testing Before Production

For major changes:
  1. Build version without setting active
  2. Test using preview frame in Behavior → Guidance
  3. Review with team if available
  4. Deploy to staging channel first (if you have one)
  5. Set as production when confident

​
Monitoring After Deployment

After each deployment:
  • First 30 minutes: Spot-check conversations manually
  • First 24 hours: Monitor key metrics (CSAT, escalation rate)
  • First week: Review conversation topics and user feedback
  • Ongoing: Compare to previous version’s metrics

​
Troubleshooting

​
Build Fails

Symptoms: “Build failed” error when creating version Common causes:
  • TODO items in advanced configuration
  • No guidance defined (or system prompt)
  • Invalid JSON in tool configuration
  • Missing required fields
Solutions:
  • Review error message for specific issue
  • Check guidance tab has at least one active guidance
  • Verify tools configuration is valid JSON
  • Remove any TODO placeholders

​
Knowledge Not Updating

Symptoms: Changes to data providers don’t appear in AI responses Cause: Haven’t rebuilt deployment with new knowledge snapshot Solution:
  1. Verify data provider synced successfully
  2. Build new version to incorporate changes
  3. Set new version as active
  4. Knowledge now available to AI

​
Channels Not Using New Version

Symptoms: Some channels show old responses after deployment Check:
  • Verify production alias was updated
  • Confirm channels are connected to production alias (not old fixed versions)
  • Clear browser cache (for website widgets)
  • Check channel configuration hasn’t changed
Solution: Usually resolves automatically within 1-2 minutes. If persisting:
  • Rebuild and redeploy
  • Check channel configuration in respective integration settings
  • Contact support if issue continues

​
Deployment Stuck

Symptoms: Build process shows “Building…” for > 5 minutes Solutions:
  • Wait up to 10 minutes (large knowledge bases take time)
  • Refresh page - may have completed
  • Check if deployment appeared in versions list
  • If still stuck after 15 minutes, try building again
  • Contact support if repeatedly failing

​
Advanced Deployment Patterns

​
Multiple Environment Setup

For teams with staging/production separation: Staging Environment:
  • Separate project for testing
  • Copy configuration from production
  • Test changes here first
  • No real customer traffic
Production Environment:
  • Main project with real customers
  • Only deploy tested changes
  • Monitor closely after updates

​
Gradual Rollout

To reduce risk of deploying changes:
  1. Deploy to one channel first:
    • Create separate alias for test channel
    • Set test alias to new version
    • Monitor for issues
    • Update production alias when confident
  2. Use separate projects for A/B testing:
    • Run two versions simultaneously
    • Route percentage of traffic to each
    • Compare metrics
    • Deploy winner to all channels

​
Automated Deployment

For advanced teams:
  • Use API to build versions programmatically
  • Trigger builds on knowledge sync completion
  • Integrate with CI/CD pipeline
  • Automated testing before production

​
Next Steps

Now that you understand deployments: Deployments give you control over when and how changes reach your users. Use this power to maintain stability while continuously improving your AI.