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61 posts about Twilio. Every summary links to the original.
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The Branded Calling trust chain, layer by layer: how identity, STIR/SHAKEN attestation, Rich Call Data, and carrier delivery combine so a verified brand name reaches the recipient's screen.
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Twilio announced general availability of its Salesforce Partner Contact Center Integration, embedding its global Super Network with over 4,800 direct carrier relationships into the native Salesforce workspace. The integration unifies omnichannel orchestration across voice, SMS, and WhatsApp using Twilio TaskRouter, routing conversations into Salesforce’s omnichannel widget while preserving existing skills-based routing rules and syncing agent presence across channels. Real-time event metadata streams into the widget before a call connects, showing recent customer activity and sentiment to reduce average handling times and eliminate repeated information requests. Carrier-grade telephony with native real-time transcription and recording splits caller and agent voices for precise transcriptions, sentiment scoring, and post-call summaries. By pairing Salesforce’s familiar interface with Twilio’s communications engine, the integration gives agents a seamless workspace with a single source of truth, eliminating tab-switching and lost context.
Building a multi-channel AI agent that remembers customers across SMS and WhatsApp is challenging because most projects require a custom memory layer; Twilio Conversations and Vercel’s eve solve this by cleanly separating short-term and long-term memory. eve holds the per-conversation transcript, while Twilio’s Memory Store persists extracted facts across sessions using automatic observation extraction from Conversation Intelligence. The tutorial walks through provisioning an Orchestrator Configuration that stitches SMS and WhatsApp into one thread, wiring a dynamic instruction that merges both memory sources, and using ngrok for local webhook tunneling. The resulting agent remembers customer context across channels and sessions, allows model swapping in one line via the AI SDK, and extends cleanly to voice and RCS without bespoke persistence code. The full sample project is on GitHub at IObert/twilio-conversations-eve-agent, and the tutorial includes provisioning steps using curl, environment variable setup, and local testing with pnpm dev.
Twilio’s Q3 2026 fraud update covers phishing trends, third-party safety, and new releases. Over 80% of phishing originating from SendGrid was due to account takeovers, with attacks centered on delivery service spoofing, invoice fraud, and targeted Japanese campaigns impersonating brands like Amazon and Mercari. Attackers used fabricated forwarded threads, typosquatted domains like tvvilio[.]org, familiar names, AI-generated email templates, and associated phone calls, sometimes spoofing Twilio’s help line. To secure third-party integrations, Twilio recommends scoping access strictly, practicing credential hygiene, and reviewing audit integrations regularly, and now recommends OAuth 2.0 Client Credentials over auth tokens or API keys for scoped short-lived tokens. New releases include IP ACL with Dry Run mode, which logs blocked requests without enforcement to prevent accidental lockouts before real enforcement.
SMS has a 98% open rate and works without internet, but sending to landlines wastes money on failed deliveries. This tutorial demonstrates filtering landlines in PHP using Twilio’s Lookup v2 API, which provides line type intelligence via the “line_type_intelligence” field. The core class extends PHP’s FilterIterator and overrides the accept() method to fetch each number’s line type, returning true only for “mobile” types and catching TwilioException on failure. The application uses Composer dependencies including monolog, twilio/sdk, and phpdotenv, loads credentials from a .env file, iterates over an ArrayIterator of phone numbers, logs each with Monolog to stdout, and sends an SMS only to mobile numbers. This approach avoids unnecessary charges and is straightforward using Twilio’s PHP helper library and SPL iterators.
A voice AI demo using Twilio Conversation Relay and FastAPI was exploited when automated clients repeatedly called its unauthenticated /api/call endpoint, generating 1,008 requests and 921 outbound calls to Israeli +972229 numbers. The incident cost $971.50 in Twilio voice usage and $10.58 in Google Gemini fees, matching International Revenue Sharing Fraud that keeps calls connected for per-minute revenue. The author used the Twilio CLI to group call records showing 920 of 921 calls targeted the same narrow Israeli range and correlated Azure Log Analytics to confirm the exploited endpoint. Calls were kept alive by automated scripts replaying conversation-extension prompts from only 541 distinct lines across 8,363 transcriptions, with some recordings mentioning happy trafficking. The post recommends authentication, duration limits, geographic permissions, signature validation, usage triggers, and demo isolation as essential controls for public voice AI apps.
Consumers rarely answer unknown numbers, causing legitimate business calls from pharmacies, banks, and delivery drivers to be ignored. Branded Calling addresses this by displaying a verified brand name, logo, and call reason on the recipient’s device to establish trust before the recipient decides to pick up. Twilio expanded Branded Calling to include AT&T (in pilot) alongside T-Mobile and Verizon, building on work since 2021 when they executed the first wireless call using Rich Call Data (RCD) over the PSTN authenticated with STIR/SHAKEN, and later documented the approach and brought the feature to general availability. Customer CareSignal, a healthcare engagement platform, saw a 21% increase in call answer rates. Twilio emphasizes that trust must extend beyond voice to channels like RCS, WhatsApp, Email, and Apple Messages for Business, so the same verified brand carries through every step.
Sharing contact details by copying text between apps is ineffective compared to sending a vCard, a structured data format supported by major operating systems and email clients. This tutorial demonstrates creating vCards in Go using the go-vcard package, which handles fields such as formatted name, structured name, street address, telephone number, email address, and URL. The code writes the vCard to a .vcf file with version 4.0 using the go-vcard encoder and constants from the package, exiting on failure. The vCard file is uploaded to Twilio Assets, a static file hosting service bundled with every Twilio account, to make it publicly accessible for the SMS. The Twilio Go SDK sends an SMS with a message body and the vCard URL as a media attachment via the Programmable Messaging API, allowing recipients to open it in their contacts app.
This tutorial demonstrates building a PHP application that records customer opt-out preferences from SMS replies using Twilio’s Incoming Message Webhook and Event Streams, which require PHP 8.5, Composer, and SQLite. When the SMS body is an opt-out keyword such as STOP, START, or HELP, Twilio includes an OptOutType parameter in the webhook request, which the application checks using strcasecmp and array_first. The application, based on the Twilio Slim Base project, stores the opt-out status and account SID in an SQLite database via PHP-DB and laminas-servicemanager, using a TableGateway for the user_optouts table. The handleWebhook() function validates the OptOutType against class constants (OPT_OUT_TYPE_START, OPT_OUT_TYPE_STOP, OPT_OUT_TYPE_HELP) and inserts a record before returning a TwiML response. Twilio already blocks further messages for standard opt-outs, but local recording enables advanced actions like syncing a CRM; the tutorial covers bootstrapping, configuring Twilio messaging services with Advanced Opt-Out, using ngrok, and verifying with an SQL query.
WebRTC provides browser APIs for real-time voice, video, and data sharing without plugins, with mandatory encryption via DTLS-SRTP and DTLS; the standard became a W3C Recommendation in January 2021. The core APIs are getUserMedia for capturing audio/video from user devices, RTCPeerConnection for peer-to-peer media exchange via offer/answer and ICE candidates, and RTCDataChannel for arbitrary data transfer. WebRTC is supported by all major browsers and used by services like Google Meet, Discord (which uses media servers for group calls to avoid expensive peer-to-peer), and AI voice agents. Twilio offers Video and Voice JavaScript SDKs that handle signaling and media relay, enabling calls to phone numbers and SIP endpoints. The post includes a camera preview example using getUserMedia that requires a secure origin and can be served with Python, then directs readers to Twilio’s quickstart tutorials for building video and voice applications.
A Twilio survey of 660 business leaders and consumers reveals a gap: 98% of organizations train AI to act more human, yet customers rank issue resolution, speed, accuracy, and availability above personality. Only 54% of consumers want human-like AI, versus 73% of brands. Behaviors customers call empathetic—acknowledging the specific situation, offering multiple solutions, using conversational language, offering compensation—depend on personalization and context, not tone. 51% of consumers find AI robotic, and 39% of businesses cite weak emotional understanding as a top dissatisfaction driver. The report recommends prioritizing context and personalization over personality, using tools like Twilio Conversation Memory and Conversation Orchestrator to make agents useful before charming.
Twilio’s Traffic Optimization Engine is a new suite for global messaging deliverability and prioritization, tackling carrier network strain from soaring volumes like the 6.9 billion messages during Cyber Week 2025. The suite automates months of manual planning, working across networks, senders, geographies, and use cases to deliver high-priority messages on time. Real-time Routing uses patented algorithms to optimize traffic across 4,800+ carrier connections every 75 seconds, while Market Throughput manages rate limits at the country and sender-type level to prevent throttling. Traffic Shaping creates dynamic lanes to prioritize one-time passwords over promotional messages, and Multitenancy fairly distributes throughput among ISV teams. Insights provides real-time analytics on deliverability and capacity allocation, and the overall system uses traffic shaping and priority queueing based on carrier, sender, and message type capabilities.
Twilio Conversation Intelligence, Conversation Orchestrator, and Conversation Memory together analyze voice calls for a Node.js voice agent built with Conversation Relay. After a call, Twilio sends a webhook to /intelligence-results containing a call summary, sentiment analysis, and script adherence for categories like introduction with the required phrase “Thanks for calling Owl Air! I’m Hoot.” The developer creates a Memory Store and Conversation Configuration, then an Intelligence rule selecting Sentiment, Summary, and Script-Adherence operators triggered at conversation end. A Node.js handler extracts the data and persists it to a SQLite database using tables for intelligence_results, operators, and operator_script_adherence_categories. Testing involves calling the Twilio number and verifying the summary, sentiment, and script adherence records in the database.
This tutorial shows PHP developers how to augment a Twilio voice AI agent with Conversation Intelligence, Conversation Orchestrator, and Conversation Memory. The goal is to retrieve a short summary of each customer call, analyze the caller’s sentiment, and check whether the agent followed set guidelines. The information is persisted to a SQLite database for later use. The tutorial builds on a previous voice agent tutorial and requires a Twilio account, a voice-capable phone number, and ngrok to expose the local server. It walks through setting up Conversation Orchestrator, Conversation Intelligence, and the application database, then testing the flow with example questions. The post also mentions the Conversations API (V2) for retrieving call summaries and sentiment analysis.
A Twilio research report identifies a 35-point satisfaction gap: 86% of brands believe their AI customer service satisfies customers, but only 51% of consumers agree. The discrepancy arises because companies measure metrics such as conversation completion surveys and containment rates, which systematically exclude abandoned or unresolved interactions. 71% of consumers abandon a conversation when the AI fails to recognize them, yet those exits rarely appear in satisfaction data. 49% of consumers say AI never resolved their issue. To close the gap, Twilio recommends tracking abandonment by conversation stage, resolution of the underlying issue across sessions, repeat contact within seven days, containment split by outcome, and escalation quality.
The Commonwealth Bank episode in 2025 demonstrated that a deflection metric is not a resolution metric: the bank reversed 45 redundancies after call volumes rose despite a voice bot credited with diverting 2,000 calls weekly. By May 2026, on a rebuilt platform, the same automation program achieved 84.6% end-to-end resolution for self-service messaging interactions. A peer-reviewed 2024 study found Whisper’s match error rate significantly higher for Australian English than American English, an effect of roughly 1.3 percentage points, with non-native accents worst affected. Australian regulation as of September 2026 imposes no affirmative AI disclosure duty, but misleading conduct provisions apply and an automated decision-making transparency obligation commences December 2026. Twilio’s platform offers an Australian region with emergency calling, model-agnostic agent execution, and a memory layer that preserves context during handoffs, addressing the containment quality gap.
Chinese enterprises expanding overseas face fragmented communication channels, strict compliance regimes, and data residency mandates across 180+ markets. A programmable communication platform (CPaaS) eliminates the need to negotiate carrier-by-carrier in every country. Twilio’s global infrastructure — 335,000+ customers, 218+ voice-capable countries, and a 99.95% API SLA — provides a single integration point for SMS, voice, email, WhatsApp, and RCS worldwide. The platform comprises five layers: programmable messaging, voice APIs, SendGrid email, Twilio Verify, and Twilio Segment. Compliance features such as 3-region data residency and email authentication help brands navigate GDPR, TCPA, and other regulations.
Rich Communication Services (RCS) upgrades SMS with branded conversations, images, carousels, and read receipts delivered through the default messaging app. Twilio Programmable Messaging supports RCS as a first-class channel, reusing the same API as SMS. This tutorial covers building an RCS campaign in Node.js, including RCS Sender registration (a manual review process with test device support), creating a twilio/card content template with dynamic variables, and broadcasting personalized messages from a JSON list. Delivery status is tracked through a status callback webhook exposed via ngrok, and replies are captured through an inbound webhook when users tap suggested reply buttons. The guide also includes troubleshooting for common issues such as messages falling back to SMS, error codes 30001 and 63001, and webhook configuration errors.
Twilio’s tutorial explains how to build an RCS Business Messaging campaign in PHP, reusing the same Programmable Messaging API used for SMS. RCS turns standard text messages into branded conversations with images, carousels, verified sender logos, suggested replies, and read receipts delivered through the recipient’s default messaging app. The walkthrough covers registering an RCS Sender, attaching it to a Messaging Service, and designing a rich card template in the Twilio Content Template Builder. It then shows how to broadcast the campaign to a recipient list, track delivery status via a status callback webhook, and capture replies through an inbound webhook. Troubleshooting guidance addresses common issues such as messages falling back to SMS, senders pending approval, and missing status callbacks.
Building enterprise-grade AI voice agents in production demands managing real-time latency, telecommunication networks, regional accents, compliance frameworks, and unpredictable customer behaviour—issues that standard text-based LLM benchmarks do not capture. The recommended approach combines Microsoft Azure for hyperscale infrastructure, Twilio for global communications, and WIZ.AI for localisation, so engineering teams avoid building low-level infrastructure and focus on unique business value. Field data from WIZ.AI across Asia reveals an ideal conversational response window of 500–800 ms, with a P90 latency under 2.0 s currently acceptable, and real-time code-switching support for languages like Singlish and Hinglish. Success metrics shift from pilot capability to commercial production benchmarks such as connection rate, recognition and tagging accuracy, and measurable business outcomes like Promise-to-Pay conversion. Engineering practices to maintain code quality include cross-model code reviews and strict pull-request line-count guardrails enforced by pre-commit hooks.
Real-world AI voice agent calls are messy, with background noise, overlapping speech, and callers interrupting mid-sentence. Twilio Conversation Relay handles interruptions through attributes like interruptible, which controls whether caller input stops the agent’s speech, and ignoreBackchannel, which filters out short backchannel phrases. Background noise that sounds like speech can cause false interruptions and garbled transcripts; Twilio’s testing found Deepgram Flux produced zero transcription failures under combined noise, while a tuned Nova-3 setup also succeeded. Turn detection uses either a traditional silence timer or Deepgram Flux’s fused model, which reduces false interruptions by roughly 30% and trims response latency. When a caller interrupts, the app receives an interrupt message with the exact text played before cutoff, allowing it to trim the LLM’s conversation history so the model only remembers what the caller heard.
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