Resources
Everything you need
to add memory to voice AI
Integration guides, platform-specific tutorials, and documentation to get persistent memory running in your voice AI stack.
Integration Guides
Platform-specific guides
Adding memory to Vapi agents
Use Vapi's function calling and post-call webhooks to sync and retrieve memories per caller.
Retell AI + Orthanc integration
Connect Retell's webhook system to Orthanc for persistent caller memory across conversations.
Bland AI memory integration
Give your Bland AI cold calling agents memory of previous conversations and prospect context.
Twilio + custom voice stack
Add persistent memory to any custom voice AI system built on Twilio or similar infrastructure.
Best Practices
Voice AI memory patterns
Caller ID strategies
Best practices for mapping phone numbers, account IDs, and session tokens to Orthanc user IDs for voice applications.
Read more →Optimizing for voice latency
How to pre-fetch context, structure system prompts, and minimize latency for real-time voice conversations.
Read more →Transcript sync patterns
When and how to sync call transcripts — post-call webhooks, real-time streaming, or batch processing.
Read more →Error handling in voice flows
Graceful degradation when memory retrieval fails during a live call. Fallback strategies and retry patterns.
Read more →Support
Need help integrating?
Building on Vapi, Retell, or a custom stack? We'll help you get memory running in your specific setup.
Common questions
How long does integration take?
Under 5 minutes for most voice platforms. Two API calls — sync and context.
Does it work with my platform?
If your platform produces call transcripts, Orthanc works with it. Vapi, Retell, Bland, Twilio, or custom.
What about latency?
Sub-200ms memory retrieval. Fast enough for real-time voice conversations without noticeable delay.