A conversation is a distributed system with a deadline
A chatbot or voice call has to resolve identity, pull live data, reason with a model, and respond — all inside a latency budget the user can feel. That makes conversational interfaces one of the least forgiving places to get architecture wrong.
Reference architectures
Chatbot Platform Architecture
Intent routing, LLM-backed dialogue management, and fallback-to-human handoff design.
IVR & Voice AI
Speech-to-text, barge-in handling, and telephony integration (SIP/PSTN) with conversational AI backends.
Mobile App Architecture
Offline-first patterns, push notification design, and secure token handling for native and cross-platform apps.
Caller & User Identity
Authenticating a caller or chat user before an agent — human or AI — is allowed to act on their account.
Omnichannel Session Continuity
Carrying context across chat, voice, and app so a customer never has to repeat themselves.
Latency & Fallback Design
Timeout budgets per turn, and graceful degradation to scripted flows when the model or a dependency is slow.
Before a conversational flow ships
- Every turn has a maximum response-time budget, with a scripted fallback if it's exceeded.
- There is always a clear, low-friction path to a human for the customer.
- Call and chat transcripts are retained and redacted according to data-privacy policy.
- Identity is verified before any account-specific action is taken, on any channel.
— Viswa