Many customer service systems still rely on outdated infrastructure that treats voice interactions as isolated events. As a result, callers often face blind transfers, disconnected data, and the frustrating experience of repeating themselves with every escalation.

In our recent LIVEWire webinar, we tackled this issue with a hands-on demo that shows how to build intelligent call flows that retain and pass context using SignalWire's AI agents, markup, and browser SDKs.

Why blind transfers ruin the customer experience

Everyone has had a negative experience with an IVR. Callers can easily get trapped in a phone tree menu where they’re unable to reach a live agent no matter what they do, causing frustration and anger. Luckily, SignalWire AI agents can help you solve this problem by modernizing your IVR to create a conversation flow that’s less frustrating for customers.

Modern customers expect more than just basic automation. They want intelligent experiences where the agent (human or virtual) knows who they are and why they called. However, traditional IVRs typically fail to capture and carry contextual data throughout the entire interaction. This disconnect leads to dropped context, increased call times, and ultimately, poor customer satisfaction.

Customers are four times more likely to leave an interaction more disloyal than when they entered it. One reason for this is because when context is rarely preserved across different stages of the call, transfers can feel like starting over. A frustrating IVR can ruin the entire customer experience.

Problem solving with Programmable Unified Communications

SignalWire introduces a radically different approach to building communication pathways with its Programmable Unified Communications (PUC) stack. Instead of stitching together integrations and static IVR menus, developers can use composable Resources such as:

• Subscribers (authenticated users)

• Scripts (declarative call flows)

• AI Agents (AI-powered digital assistants)

• Call flows (voice routing logic)

• Rooms (voice or video conferencing spaces)

At the heart of it all is SignalWire Markup Language (SWML), a YAML or JSON-based script that allows developers to build sophisticated logic, invoke AI agents, and react to user input in real time. This means you can define workflows where calls are dynamically routed based on data lookups, caller input, or AI-detected intent.

Most AI implementations in telecom today are bolted onto legacy stacks. This introduces issues like latency. SignalWire, by contrast, embeds AI into the media layer itself. This architectural choice allows for sub-500ms latency, context persistence, and real-time decision-making.

Tools like Datasphere (SignalWire's RAG API) can be layered into these flows, letting your AI agents pull in fresh information from your documentation or knowledge bases at the moment it's needed.

Building context-aware call flows

If you're interested in following the demo and building context-aware call flows, here's what you'll need:

• A SignalWire account (with subscriber authentication enabled)

• An ngrok account for exposing localhost

• Python 3.8+ for your server-side logic

• A SignalWire AI Agent

You can define your prompts using YAML or JSON and attach them to any callable resource. Then, configure your phone number or SIP endpoint to use that resource, and test the call end-to-end from your browser. View the GitHub repo here.

LIVEWire demo: Real-time context transfer

An AI agent can perform tasks like verifying customer membership and summarizing issues using structured prompts. The demo showcases this full end-to-end experience of intelligent context-aware call routing:

1. A user calls support from a browser app.

2. An AI agent answers the call, verifies the caller's identity using a member ID, and confirms their premium support status.

3. The AI gathers a real-time summary of the caller's issue ("I'm getting a 404 error"), performs a CRM lookup, and packages all this information.

4. The data is sent to a live agent, showing up in a browser client in real time as the call is transferred.

5. The agent receives the call with full context intact, eliminating the need for repeated questions and significantly speeding up resolution time.

How it works

The SignalWire AI Gateway

One of the most powerful tools in this stack is the SignalWire AI Gateway (SWAIG). It allows developers to define serverless functions that an AI agent can call mid-conversation. These functions can do things like:

• Validate customer information

• Query a database

• Send context data to a CRM

• Load new call logic dynamically

With SWAIG, your AI agents go from passive responders to proactive assistants that can complete tasks and coordinate with your business systems in real time.

Call deflection

One of the most immediate benefits of context-aware AI call flows is effective call deflection. Instead of routing every call to a live agent, AI agents can triage incoming interactions, resolve simpler requests autonomously, and escalate only when necessary.

AI agents can verify a customer's identity, pull up recent order details, and answer questions all without human intervention. If the issue can't be resolved, it can still pass along the full context for a seamless handoff to a live agent.

The AI agent can also recognize DTMF input and simulate it, meaning it can navigate external IVRs or capture digits mid-call if needed. This ability makes the platform interoperable with traditional systems while still bringing AI advantages.

Best practices for contextual AI call flows

To build a high-quality voice AI experience, here are a few tips from SignalWire experts:

• Structure your prompts with intent. Separate personality, goals, and instructions. This improves consistency and reduces hallucinations.

• Validate callers early using SWAIG to confirm identities or fetch necessary data before escalation.

• Handle failures gracefully by including fallbacks for missing data or misunderstood queries.

When done right, AI agents significantly improve IVRs by reducing call volume for support teams and accelerating resolution times to increase overall customer satisfaction.

The future of voice is programmable, contextual, and AI-native. And with SignalWire, it's already here. Sign up for a space today to start a free trial.