How to Build a Real-Time Agent Assist API for Live Calls

Bolti is a voice AI platform for building production-ready conversational phone agents that helps businesses automate outbound sales, customer support, and HR screening. While fully autonomous AI voice agents can handle entire calls end-to-end, many companies prefer a hybrid approach: human agents talking to customers, guided behind the scenes by a real-time agent assist API. With Bolti's ₹6/min pay-as-you-go pricing and low-latency architecture, you can build live assist cards that listen to active calls and feed your human agents the exact answers, scripts, or customer data they need right when they need it.

Unlike traditional post-call QA that catches mistakes after a call ends, real-time agent assistance prevents mistakes as they happen. If a customer asks a complex technical question or brings up a competitor, a real-time system pushes an assist card to the human agent's screen in under a second.

What is a real-time agent assist API?

A real-time agent assist API is a system that streams live call audio to a speech-to-text engine, processes the transcript using a Large Language Model (LLM), and instantly pushes helpful context, answers, or checklists to a human agent's dashboard during a live call.

Traditional agent assist systems rely on manual keyword triggers or slow batch processing. A modern real-time agent assist API leverages the same underlying voice pipeline used by fully autonomous AI voice agents to deliver sub-second, context-aware guidance.

By hooking into the live stream of a call, the API can:

• Transcribe customer speech instantly using high-speed STT engines.
• Analyze sentiment, intent, and complex product queries on the fly.
• Fetch internal knowledge base documents automatically.
• Display structured UI "cards" on the agent's screen with step-by-step troubleshooting guides or handling scripts.

How the voice pipeline powers live agent assist

To build a reliable agent assist API, you need a high-performance voice pipeline. The architecture is identical to the pipeline used to power Bolti's autonomous agents, but instead of synthesizing voice output back to the caller, the pipeline outputs structured text data to the agent's screen.

The core pipeline runs the following loop multiple times per second:

1. Audio Streaming: The active call's audio is split into two streams (caller and human agent) and streamed via SIP/WebRTC.
2. Speech-to-Text (STT): High-speed engines transcribe the audio in real time.
3. LLM Processing: The live transcript, along with system prompts and dynamic context, is sent to an LLM.
4. Tool/API Call: The LLM decides if it needs to query internal CRM data or a knowledge base.
5. Assist Card Delivery: The final response is pushed to the agent's front-end UI via WebSockets.

Because Bolti is built for production phone calls, this entire loop benefits from telephony-grade noise cancellation and sub-second turn-taking optimization, ensuring that assist cards appear on screen before the customer even finishes their sentence.

Step-by-step: Building real-time assist cards

Building an assist card system requires connecting your telephony layer, your transcription/LLM engine, and your agent desktop UI. Here is how you can set this up using a real-time agent assist API.

Step 1: Establish the live audio stream

To analyze a call, you must capture the audio stream. You can do this by bringing your own SIP trunk (BYOC) through providers like Twilio, Plivo, or Exotel, or by utilizing Bolti's native telephony integrations. When a call connects, you initiate an audio fork (SIPREC or media streams) that sends the dual-channel audio (caller and agent) directly to your real-time processing server.

Step 2: Configure the real-time transcription

Run the incoming audio through a low-latency STT engine. For Indian businesses, managing multilingual conversations is crucial. Your STT engine must support code-switching (like Hinglish) and regional languages. Bolti supports over 80 global languages and regional Indian dialects, ensuring accurate transcription even with heavy line noise.

Step 3: Prompt the LLM for structured assistance

Instead of asking the LLM to write a conversational reply, prompt it to output structured JSON designed for your human agent's UI.

Your system prompt should instruct the LLM to monitor for specific triggers:

• Competitor mentions: Trigger a comparison card.
• Technical troubleshooting: Fetch the exact steps from your product docs.
• Compliance requirements: Remind the agent to read mandatory disclaimers.

Here is an example of a structured JSON payload your API can push to the front-end:

{
  "card_type": "competitor_battlecard",
  "title": "Competitor Alert: Acme Corp",
  "talking_points": [
    "We offer 24/7 phone support; Acme only offers email.",
    "Our platform includes native DPDP compliance out of the box.",
    "Mention our ₹6/minute pay-as-you-go pricing to counter their annual lock-in."
  ],
  "suggested_script": "I understand you are looking at Acme Corp. Many of our customers switched from them because we offer 24/7 phone support and a flexible pay-as-you-go model with no annual lock-in. Would you like to see how our pricing compares?"
} 

Step 4: Push to the agent's desktop via WebSockets

Your front-end application (whether a custom CRM, Salesforce widget, or Zoho integration) should listen to a WebSocket connection. When the API emits a new structured assist payload, the front-end instantly renders a slide-out card or highlights a checklist on the agent's screen.

Key use cases for live assist cards in 2026

Implementing a real-time agent assist API dramatically improves key call center metrics like First Call Resolution (FCR) and Average Handle Time (AHT). Here are some of the most common applications:

• Sales enablement: Guide BDRs through complex objections, pricing structures, and competitor comparisons during live discovery calls. For more ideas on structuring sales scripts, check out our sales enablement use cases.
• Support and troubleshooting: Help support representatives diagnose hardware or software issues by automatically surfacing the correct debugging steps based on what the customer describes.
• Compliance and quality assurance: Ensure agents read mandatory legal disclosures, verify customer identities correctly, and follow script guidelines in highly regulated industries like fintech and healthcare.
• Multilingual translation: Provide real-time translation hints on screen when an agent is speaking with a customer in a different regional language.

Set up your first real-time agent assist system

Building a real-time agent assist API doesn't have to take months of development. With Bolti, you can leverage a production-grade voice pipeline, low-latency STT, and built-in telephony tools to start streaming live call data and generating assist cards immediately.

You can sign up for a free trial and get 50 free minutes of call time to test your integrations, configure your prompts, and build your first live assist prototype.

Ready to empower your human agents with real-time AI guidance? Get 50 free minutes and start building today.

Frequently Asked Questions

What is the latency of a real-time agent assist API?

With Bolti's optimized voice pipeline, the latency from the moment a caller finishes speaking to when an assist card can be generated and pushed to an agent's screen is under one second (sub-second latency).

Does Bolti support regional Indian languages for real-time transcription?

Yes. Bolti is an India-first, multilingual platform that supports Hindi, Marathi, Tamil, Telugu, Bengali, Gujarati, English, and over 80 global languages, making it highly accurate for regional dialects and code-switched languages like Hinglish.

Can I use my own telephony provider with Bolti?

Yes. Bolti supports Bring Your Own Carrier (BYOC). You can register your own SIP trunk using providers like Twilio, Plivo, Exotel, or Vobiz, or purchase phone numbers directly through Bolti.

How much does it cost to run Bolti's voice pipeline?

Bolti offers a simple pay-as-you-go pricing model at ₹6 per minute, with no hidden fees or heavy upfront commitments. You can also start with a free trial that includes 50 minutes of call time.