Plivo can provide the telephone number, call control, and carrier connectivity while your application supplies the conversational intelligence. To connect a voice agent to a Plivo phone number, you need a reliable path between Plivo, an orchestration service, and your speech and language models.
The architecture is straightforward:
- Telephony layer: Plivo receives or places the call.
- Orchestration layer: Your server validates webhooks, controls call flow, manages sessions, and connects services.
- AI layer: Speech-to-text (STT), an LLM, and text-to-speech (TTS) produce the conversation.
- Business systems: CRM, ticketing, appointment, payment, or order APIs provide context and execute actions.
This setup is useful for support lines, appointment confirmation, lead qualification, collections, and Indian-language call flows. If you are still evaluating the category, start with this overview of what a voice agent is before choosing an implementation path.
Choose the right connection method
There are two practical ways to connect Plivo to an AI agent.
WebSocket media streaming
Use bidirectional media streaming when you own the orchestration layer or need precise control over audio, interruption handling, transcripts, and business logic. Plivo sends call audio to your secure WebSocket endpoint; your service passes it to STT and returns generated speech to the call.
This option is usually best when:
- You need custom routing, authentication, or CRM actions.
- You want to switch STT, LLM, or TTS providers independently.
- You need detailed observability and conversation logs.
- Your team can operate a low-latency, always-on media service.
SIP connectivity
Use SIP when your agent platform exposes a SIP address or when your organisation already operates a SIP or contact-centre environment. Plivo can route calls to the agent through call-control instructions, while the platform manages much of the media pipeline.
SIP can reduce engineering effort, but confirm codec support, authentication, failover, call transfer, recording, and billing behaviour before committing. For a broader vendor comparison, see this guide to top-rated voice agent services for Indian businesses.
Prerequisites
Prepare these components before configuring the phone number:
- A verified Plivo account and an active voice-enabled number.
- A public HTTPS endpoint for the answer webhook.
- A WSS endpoint if you are streaming media.
- A session store such as Redis, a database, or a managed conversation platform.
- API credentials for STT, LLM, and TTS providers.
- A clear call policy: greeting, authentication, allowed actions, escalation rules, and hang-up conditions.
- A test number and a production number kept separate.
Do not put provider keys in browser code or hard-code them in a repository. Store secrets in a managed secret store, rotate them, and limit each credential to the permissions it requires.
Configure the Plivo application
In the Plivo Console, create or select a Voice Application and assign it to your phone number. Set the Answer URL to your HTTPS endpoint. Plivo will request this URL when an inbound call is answered; your server must return valid Plivo XML quickly.
A minimal streaming response looks like this:
<?xml version="1.0" encoding="UTF-8"?>
<Response>
<Stream url="wss://voice.example.com/plivo/media" />
</Response>Use the exact streaming and audio attributes supported by the current Plivo documentation and your account configuration. Treat the answer endpoint as a production API: validate requests where supported, return the correct content type, log a request ID, and respond within a predictable time budget.
For outbound calls, create the call through Plivo’s Voice API and provide an answer_url. When the called party answers, Plivo fetches the same type of XML instructions. Keep inbound and outbound call policies separate: outbound campaigns may require consent, frequency limits, list hygiene, and additional regulatory review.
Build the WebSocket media pipeline
Your media server should process each call as a stateful session. A typical sequence is:
1. Accept the WebSocket connection and identify the call and stream.
2. Decode the incoming event and extract the audio payload.
3. Convert audio only when required by the STT provider.
4. Run voice activity detection or provider-native turn detection.
5. Send speech frames to STT and receive partial and final transcripts.
6. Pass the final user turn, conversation state, and permitted tools to the LLM.
7. Stream the response into TTS rather than waiting for the complete answer.
8. Encode the returned audio in the format expected by the Plivo stream.
9. Send audio frames back while continuing to listen for interruption.
Keep media handling separate from business logic. The media loop should remain responsive even when a CRM request or LLM call is slow. Use bounded queues, timeouts, cancellation, and backpressure so one stalled dependency cannot exhaust memory or block other calls.
Audio mismatches are a common source of distorted speech and failed recognition. Telephony commonly uses narrowband 8 kHz codecs such as G.711 μ-law, while AI services may expect linear PCM at another sample rate. Confirm the codec, sample rate, byte order, and framing for every provider. Avoid repeated transcoding; decode once at the boundary and encode once before playback where possible.
Implement SIP routing when appropriate
If your voice platform gives you a SIP URI, route the call through Plivo’s SIP-compatible call flow. A conceptual XML pattern is:
<Response>
<Dial>
<User>sip:agent@example.com</User>
</Dial>
</Response>The exact Plivo XML, endpoint format, and authentication method depend on the platform. Test both directions, DTMF, caller ID, transfers, early media, and failure responses. Configure a fallback destination so a SIP timeout does not leave callers in silence.
For teams building rather than buying, staffing matters as much as telephony configuration. This guide to hiring voice agent developers covers the skills needed across audio, backend, integrations, and evaluation.
Reduce latency and improve conversation quality
A voice agent feels slow when any part of the chain waits unnecessarily. Measure each stage separately: Plivo-to-server, STT finalisation, LLM first token, TTS first byte, and audio playback. Useful production targets are service-specific, but design for fast first audio and graceful progress messages rather than relying on a single total-latency number.
Prioritise these controls:
- Host the media service near your users and relevant provider regions; Mumbai is a sensible starting point for many India-focused deployments.
- Use streaming STT, incremental LLM output, and streaming TTS.
- Keep prompts short and retrieve only the business data needed for the current turn.
- Use endpointing and barge-in detection so callers do not wait through long silences.
- Cancel unfinished LLM and TTS work when the caller interrupts.
- Cache stable prompts, greetings, and frequently used responses.
- Set timeouts and fallback phrases for every external dependency.
Never optimise latency by removing confirmation for risky actions. A fast agent that sends the wrong refund or appointment is not production-ready.
Production safeguards for India
Before launch, document how the agent handles consent, caller identification, sensitive information, recordings, and escalation. For Indian deployments, review applicable TRAI requirements, calling permissions, DND or NDNC obligations, telecom-provider rules, and sector-specific requirements. Do not assume that an AI voice call is exempt because it is automated.
Apply the Digital Personal Data Protection Act obligations relevant to your processing, including purpose limitation, access controls, retention, deletion, and vendor governance. Mask payment details and identity documents in logs. Encrypt recordings and transcripts, restrict staff access, and define a retention schedule instead of storing every call indefinitely.
Design language support deliberately. Hindi, English, and regional-language calls can involve code-switching, names, addresses, and noisy mobile networks. Test with real accents and realistic interruptions, and provide DTMF or human-agent fallback for callers who cannot complete the interaction by voice.
Testing checklist
Before moving the number to production, test:
- Inbound answer, hang-up, transfer, voicemail, and timeout paths.
- Outbound caller ID, consent, retry limits, and opt-out handling.
- Silence, background noise, accents, code-switching, and overlapping speech.
- Barge-in while the agent is speaking.
- Invalid audio, dropped WebSockets, duplicate events, and provider retries.
- CRM outages, LLM timeouts, TTS failures, and rate limits.
- Recording permissions, transcript redaction, and data deletion.
- Concurrent calls, peak traffic, cost per minute, and alert thresholds.
Start with a narrow, low-risk workflow and a human escalation path. Expand only after reviewing transcripts, failure reasons, containment rate, transfer rate, latency, and customer feedback. A voice agent should be judged on completed outcomes and safe handoffs—not merely on whether it answered the phone.