Conversational AI

Build contact center infrastructure for the AI era

Strategic infrastructure for AI-era contact centers: cloud architecture, unified data, and low-latency voice.

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By 2025, 80% of customer service organizations will use generative AI to improve agent productivity and customer experience, according to Gartner. Yet most contact centers run on infrastructure built for a different era: siloed systems, public internet routing, and architecture that treats AI as an afterthought.

The result? Latency that makes Voice AI conversations feel robotic. Data that doesn't flow between systems. Outages that take down entire operations.

This guide covers the infrastructure choices that separate contact centers ready for AI from those that will struggle to keep up.

Why infrastructure decides AI success

Traditional contact center infrastructure was built when human agents handled every interaction, "multichannel" meant phone plus email, and data lived in silos.

That legacy architecture creates friction when you try to implement AI:

  • Latency kills Voice AI. Even 300ms of delay makes conversations feel unnatural. If audio travels over the public internet through multiple hops, you'll hit that threshold.
  • Missing context breaks automation. Without real-time access to customer history, AI systems guess instead of act.
  • Single points of failure become outages. One region goes down, your entire contact center goes dark.

In practical terms, infrastructure decides:

  • How fast a caller hears a response
  • Whether calls stay clear during traffic spikes
  • Whether customer history is available mid-conversation
  • Whether your contact center survives provider or regional outages

Core layers of contact center infrastructure

Most contact centers include three layers:

Layer Components
Hardware/Endpoints Agent desktops, headsets, SIP devices, browser clients
Software Routing, workforce management, QA tooling, agent assist, analytics
Telecommunications PSTN connectivity, SIP trunking, internet and private networking

AI-ready contact centers add:

  • Real-time speech analytics and transcription
  • Data pipelines syncing context to CRM and ticketing
  • Observability for jitter, packet loss, and post-dial delay

What separates basic setups from AI-ready ones is how these layers connect and perform in production.

Five strategic infrastructure choices

1. Cloud-native and distributed architecture

Cloud infrastructure can spin up resources on demand, crucial for handling the variable loads AI systems create. But design matters more than "being in the cloud."

What goes wrong with poor cloud design:

  • Audio travels too far between telephony, media, and AI compute, creating lag
  • Calls route over public internet and pick up jitter and packet loss
  • A single region outage becomes a customer-facing outage
  • Traffic spikes trigger hold times and degraded audio

What good architecture looks like:

  • Telephony points of presence, media services, and AI compute located close together
  • Traffic distributed across multiple regions
  • Multi-cloud failover designed upfront

How Telnyx enables this:

Telnyx routes voice over a privately owned, multi-cloud IP backbone. Traffic stays off the public internet, reducing jitter and packet loss for consistent call quality worldwide.

When a region or cloud provider experiences an outage, traffic automatically fails over. Support stays online without customer impact. The private network architecture maintains the low latency essential for natural Voice AI conversations: under 250ms round-trip for most global routes.

2. Unified data architecture

AI systems are only as good as the data they can access. If customer context isn't available in real-time, automation becomes guesswork and agents do extra work.

What strong data integration unlocks:

  • Less copy-paste for agents
  • Fewer transfers caused by missing data
  • More accurate automation based on real customer history
  • Cleaner reporting and QA with consistent outcome capture

How Telnyx enables this:

Telnyx provides APIs and event-driven workflows that connect to CRM, ticketing, and internal systems.

When a call starts, you can automatically fetch the customer record, open a ticket, and log the outcome without manual intervention.

Example: When Voice AI identifies a high-priority customer, it retrieves their complete history from your CRM, checks open tickets, and routes them to a specialized team before a human agent picks up. Agents spend less time hunting for information.

3. Real-time call control

Modern contact centers need infrastructure that responds to what's happening in a conversation as it happens.

What to look for:

  • Event-driven call control with webhooks
  • Stateful IVRs with retries and timeouts
  • Routing decisions based on DTMF and speech input
  • Escalation paths that preserve context for agents

How Telnyx enables this:

Telnyx offers programmable call control using real-time events and webhooks. Update routing logic or business hours in code rather than rebuilding visual flows.

When a call event occurs, whether it's DTMF input, speech recognition, or an AI decision point, your application receives a webhook and responds with commands to control the call.

You can implement logic like: routing based on customer tier, adjusting wait messaging based on queue depth, or changing AI behavior based on conversation sentiment.

SIP and WebRTC run side by side. Operate browser-based agent desktops and traditional SIP endpoints from the same platform.

4. Voice AI with low-latency media

Voice AI handles routine requests, guides callers, and provides 24/7 availability. It reduces wait times and scales without adding headcount for every demand increase.

Why latency matters:

For voice interactions, even small delays make conversations feel unnatural. Research shows humans perceive delays above 300ms as awkward pauses. Low-latency infrastructure is essential for AI responses that feel immediate.

What AI-ready infrastructure requires:

  • Sub-300ms audio round-trip
  • Flexible model switching (STT, TTS, LLM) without rebuilding call flows
  • Seamless handoffs to human agents with full conversation context

How Telnyx enables this:

Telnyx's telephony points of presence and low-latency media handling are designed for real-time voice. Voice AI agents answer, capture intent, and respond naturally without awkward pauses.

The infrastructure minimizes distance between telephony endpoints, media processing, and AI compute to keep latency under human perception thresholds.

You have access to multiple STT, TTS, and LLM providers. Switch between them with a single parameter change. No need to rebuild call flows when testing new speech recognition models or changing text-to-speech voices.

When conversations need to escalate, real-time call control enables seamless handoffs. Agents receive complete conversation context. Customers don't repeat themselves.

5. End-to-end observability

You can't improve what you can't measure. AI-era infrastructure requires visibility across the entire call path: from customer endpoint through network to AI systems and agents.

What to monitor:

  • Quality metrics: jitter, packet loss, latency, post-dial delay
  • Conversation data: transcription, sentiment, outcomes
  • System performance: API response times, webhook delivery, AI model latency

Why it matters:

When a customer reports poor call quality, you need to determine whether the problem is network-related, carrier-related, or in your application layer. Without granular visibility, troubleshooting becomes guesswork.

How Telnyx enables this:

Telnyx provides end-to-end voice monitoring across the entire call path. Pinpoint whether quality issues originate from carrier, region, endpoint, or AI layer.

Launch support in new countries while maintaining consistent audio quality and call completion rates. Track regional performance variations.

Human-AI collaboration

The future isn't replacing agents entirely. It's augmenting human capabilities with AI assistance.

This requires infrastructure that:

  • Supports seamless handoffs between AI and humans
  • Provides agents with AI-generated insights in real-time
  • Enables supervisors to monitor both human and AI performance

Agent desktops need to evolve beyond CRM screens into AI-powered command centers that surface relevant information, suggest responses, provide real-time summaries, and automate routine tasks. The infrastructure must support this with low latency, high reliability, and intelligent information prioritization.

Security and compliance by design

AI introduces new security and compliance considerations that must be baked into infrastructure from day one.

What AI-era security requires:

  • End-to-end encryption for customer data flowing through AI systems
  • Granular access controls limiting what each AI component can see and do
  • Audit trails demonstrating compliance with AI usage, data privacy, and consent regulations
  • Data residency management for regional requirements
  • Automated compliance reporting
  • Ability to respond to new regulatory requirements without overhauling systems

Strategic infrastructure incorporates security and compliance controls at every layer, rather than treating them as afterthoughts.

The migration path

For organizations with existing contact center infrastructure, a complete rip-and-replace approach is rarely feasible.

A phased migration strategy works better:

  1. Identify the highest-value use cases for AI
  2. Build infrastructure to support those use cases first
  3. Start with a cloud-based AI layer that sits alongside legacy systems
  4. Gradually shift functionality to new infrastructure as business value becomes clear
  5. Maintain a coherent long-term vision while taking pragmatic steps

Telnyx supports this model with programmable call control and event-driven workflows, giving teams the flexibility to evolve their contact center experience while keeping performance and reliability consistent.

Benefits of strategic infrastructure

Benefit What it enables Example
Better customer experience Shared context across channels and between AI and human agents A caller starts with Voice AI, then escalates to an agent who sees the summary and customer record immediately
Higher efficiency Faster routing, fewer manual steps, fewer unnecessary transfers Call outcomes and notes log automatically to CRM and ticketing, reducing after-call work
Scalability and reliability Distributed capacity, regional resiliency, failover During quarter-close spikes, traffic scales without long hold times; service stays online through regional outages
Actionable insights Clean data capture for coaching, forecasting, and optimization Transcription and analytics reveal repeat contact drivers, helping teams adjust routing and train agents

The strategic advantage

Organizations that build contact center infrastructure strategically for the AI era can:

  • Deploy new AI capabilities faster
  • Adapt to changing customer expectations more readily
  • Operate more efficiently than competitors locked into legacy architectures

More importantly, they position themselves to take advantage of AI innovations that haven't been invented yet. The infrastructure decisions you make today shape your customer service capabilities for years to come.

Power your contact center with Telnyx

Modern contact centers depend on infrastructure that supports 24/7 availability, real-time voice performance, AI workflows, and personalization across systems. Telnyx provides the building blocks to run these experiences reliably at scale.

Whether you're modernizing an existing contact center or building from scratch, Telnyx gives you a foundation for intelligent, personalized, 24/7 customer interactions with the performance and flexibility required for Voice AI. See how PatientSync built their call flow with Telnyx.


Learn more how Telnyx can help you build your own AI ready contact center. Talk to our team to see how Telnyx fits into your contact center infrastructure roadmap.
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Deniz-Yakışıklı-Avatar
Deniz Yakışıklı

Sr. Product Marketing Manager

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