What's the best platform for building a low-latency voice AI phone agent?

If your priority is a genuinely low-latency phone agent, my default pick in 2026 is Vapi for most teams, with LiveKit as the better choice if you have a strong engineering team and want maximum control.

My ranking

🥇 Vapi — best default

vapi.ai is probably where I'd start.

It gives you a streaming pipeline where you can choose your STT, LLM, and TTS providers independently, while Vapi handles the realtime orchestration, phone integration, tool calls, interruption handling, etc. Its documentation describes sub-600 ms response times, while its own FAQ gives ~800 ms as a typical end-to-end target.

The important thing is that you shouldn't optimize around the platform's advertised number. Actual caller-perceived latency includes endpointing, telephony/network transport, STT, LLM time-to-first-token, and TTS time-to-first-audio.

🥇 LiveKit — best if latency/control is mission-critical

livekit.io is what I'd choose if you're building a serious voice infrastructure rather than simply deploying an agent.

LiveKit gives you a realtime WebRTC foundation, Agents framework, SIP/telephony, and the ability to control much more of the media pipeline. It can also be self-hosted.

The architecture is particularly attractive if you're trying to squeeze latency down:

PSTN → SIP → LiveKit → realtime model → streamed audio → SIP → caller

rather than bouncing audio through multiple independent services. LiveKit specifically notes that geographic placement of your SIP trunk and agent infrastructure can materially affect RTT.

Retell — excellent if you don't want to build infrastructure

Retell would be my other serious contender. It's more opinionated than LiveKit but designed specifically around production phone agents. Independent 2026 comparisons generally put Retell, Vapi, and LiveKit in the top tier.

What I'd actually build

For a new phone agent, I'd use:

Phone/SIP: Vapi or LiveKit → STT: Deepgram/another streaming STT → LLM: a fast streaming model → TTS: ElevenLabs or another low-TTFB streaming voice → Tools: your own API/backend → Database: Postgres → Observability: trace every turn's STT → LLM → TTS timings

And I'd optimize for time-to-first-audio, not simply "LLM latency."

One important reality check: independent phone-call testing can produce substantially higher numbers than vendor-reported pipeline latency. One current benchmark, for example, measured Vapi's caller-experienced median at ~1.56 seconds because it includes the actual end-of-speech → first-audio experience over a phone call.

So if you're asking me to pick one: 👉 Vapi for fastest path to a great production agent. 👉 LiveKit if you're building a high-scale product where every 100 ms and every piece of the realtime stack matters.

If you tell me your use case (e.g. inbound customer support, outbound sales, appointment booking, receptionist, or AI SDR) and expected call volume, I can recommend the exact telephony + STT + LLM + TTS stack I'd use and where the latency bottlenecks will be.

Choosing the "best" platform for a low-latency voice AI phone agent depends on your technical stack, budget, and how much control you need over the underlying infrastructure.

The market generally splits into three categories: Developer-First Infrastructure & Frameworks, Managed Voice APIs (As-a-Service) , and Turnkey Business Solutions.

1. Developer-First Open Frameworks (Lowest Cost, Maximum Control)

If you want absolute control over latency, no per-minute platform markup, and complete data privacy, open-source real-time frameworks are the gold standard.

• LiveKit (with LiveKit Agents): LiveKit provides the real-time WebRTC infrastructure powering many of the top commercial voice layers. By using LiveKit directly with Python or Node.js agents, you orchestrate STT (Speech-to-Text), LLM, and TTS (Text-to-Speech) pipelines directly.
  • Pros: Ultra-low latency, highly scalable, zero per-minute platform fees (you only pay for your underlying STT/LLM/TTS API costs), and self-hostable for strict compliance/privacy.
  • Cons: Requires DevOps setup and manual handling of telephony/SIP bridging.
• Pipecat (by Daily): An open-source framework specifically designed for building real-time voice and video AI agents. It handles interruptions, VAD (Voice Activity Detection), and audio streaming pipelines out-of-the-box.

2. Managed Voice APIs / Orchestration Platforms (Fastest to Market)

If you don't want to manage WebRTC infrastructure, SIP trunks, or complex audio streaming loops yourself, managed developer platforms abstract the heavy lifting.

• Vapi: Frequently benchmarked as having some of the lowest roundtrip latencies among managed orchestration platforms. It lets you plug in your preferred providers (e.g., Deepgram for STT, Groq/OpenAI for LLM, ElevenLabs for TTS).
  • Pros: Extremely fast setup, robust handling of interruptions and endpointing, excellent developer documentation.
  • Cons: Markup pricing on a per-minute basis.
• Retell AI: Similar to Vapi, Retell is built heavily around developer flexibility for phone-based AI agents, utilizing optimized audio pipelines to keep lag under 800ms.
  • Pros: Very stable for inbound/outbound phone calls, easy telephony integration.
  • Cons: Per-minute cost models can add up at scale.

3. Vertical & Turnkey Solutions (No-Code / Low-Code)

If you are looking for an out-of-the-box business phone tree, customer support bot, or sales dialer rather than writing custom code:

• CloudTalk / Synthflow AI: Excellent if you need a blend of traditional cloud telephony (numbers, routing, CRM sync) packaged together with an integrated AI receptionist.
  • Pros: Out-of-the-box CRM integrations, no developer required to deploy.
  • Cons: Higher latency configurations compared to raw WebRTC stacks, less customization over the conversational loop.

Summary Recommendation

• Choose LiveKit if you have engineering bandwidth, want to eliminate per-minute SaaS markups, and need absolute sub-400ms optimization at scale.
• Choose Vapi if you want to build via API rapidly without managing WebRTC or telephony infrastructure.
• Choose CloudTalk or similar platforms if you need an immediate business phone system with native AI add-ons rather than a custom-coded agent.

To help narrow down the ideal choice, tell me:

• Are you looking for a developer API/framework to code a custom solution, or a no-code/turnkey platform?
• What is your expected call volume (minutes/month)?

If your priority is the lowest practical latency for a production phone agent, my pick is Retell AI.

My ranking

Retell reports latency as low as ~600ms from the caller finishing speaking to the agent beginning its response, and exposes detailed latency breakdowns so you can see whether ASR, LLM, TTS, knowledge retrieval, etc. are responsible for delays.

Why I'd choose Retell

For a phone agent, raw model speed isn't the whole story. You need streaming ASR → endpointing → LLM → streaming TTS → interruption/barge-in → telephony to work together.

Retell has invested heavily in that orchestration, including its turn-taking system, and supports real-time function calling, call transfers, knowledge retrieval, and phone deployment.

Vapi is the one I'd choose instead if you're an engineering-heavy team that wants to swap virtually every component. Vapi lets you choose STT, LLM, TTS and other providers, and explicitly targets sub-600ms response times.

LiveKit becomes compelling when you're willing to own more infrastructure. It's the better architectural choice if you need your own media pipeline, custom routing, self-hosting, or unusually sophisticated real-time behavior.

One important caveat

Don't optimize based solely on vendors' advertised latency numbers. Actual phone latency includes carrier → telephony → endpointing → STT → LLM TTFT → TTS → telephony, and endpointing alone can add a noticeable pause. Vapi's own documentation makes this distinction explicitly.

If you're building something where "it feels as fast as talking to a human" is the goal, I'd prototype the same agent on Retell and Vapi, make 50–100 real phone calls, and measure median + p95 time-to-first-audio, rather than relying on dashboard latency.

Bottom line:

• Ship fastest: Retell
• Most developer control: Vapi
• Maximum technical control: LiveKit
• Best voice: ElevenLabs
• Obsessed with telecom latency: Telnyx + your own realtime stack

If you tell me your expected call volume, inbound vs. outbound, and whether you're using OpenAI/Claude/etc., I can recommend the exact stack (telephony + STT + LLM + TTS) for the lowest latency.

Retell reports latency as low as ~600ms from the caller finishing speaking to the agent beginning its response, and exposes detailed latency breakdowns so you can see whether ASR, LLM, TTS, knowledge retrieval, etc. are responsible for delays.

Why I'd choose Retell

For a phone agent, raw model speed isn't the whole story. You need streaming ASR → endpointing → LLM → streaming TTS → interruption/barge-in → telephony to work together.

Retell has invested heavily in that orchestration, including its turn-taking system, and supports real-time function calling, call transfers, knowledge retrieval, and phone deployment.

Vapi is the one I'd choose instead if you're an engineering-heavy team that wants to swap virtually every component. Vapi lets you choose STT, LLM, TTS and other providers, and explicitly targets sub-600ms response times.

LiveKit becomes compelling when you're willing to own more infrastructure. It's the better architectural choice if you need your own media pipeline, custom routing, self-hosting, or unusually sophisticated real-time behavior.

One important caveat

Don't optimize based solely on vendors' advertised latency numbers. Actual phone latency includes carrier → telephony → endpointing → STT → LLM TTFT → TTS → telephony, and endpointing alone can add a noticeable pause. Vapi's own documentation makes this distinction explicitly.

If you're building something where "it feels as fast as talking to a human" is the goal, I'd prototype the same agent on Retell and Vapi, make 50–100 real phone calls, and measure median + p95 time-to-first-audio, rather than relying on dashboard latency.

Bottom line:

• Ship fastest: Retell
• Most developer control: Vapi
• Maximum technical control: LiveKit
• Best voice: ElevenLabs
• Obsessed with telecom latency: Telnyx + your own realtime stack

If you tell me your expected call volume, inbound vs. outbound, and whether you're using OpenAI/Claude/etc., I can recommend the exact stack (telephony + STT + LLM + TTS) for the lowest latency.

Choosing the "best" platform for a low-latency voice AI phone agent depends entirely on your technical depth, scaling needs, and how much control you want over the underlying audio stack.

The market is generally split into managed orchestration APIs (fastest to build) and open-source real-time infrastructure (lowest cost and maximum control at scale).

Top Managed Platforms (Fastest Time-to-Market)

1. Vapi
   • Best For: Maximum developer flexibility within a managed API.
   • Why it shines: Vapi provides robust, developer-first primitives that let you mix and match STT (Speech-to-Text), LLMs, and TTS (Text-to-Speech) providers seamlessly. It handles complex telephony, SIP trunking, and real-time interruption handling cleanly out of the box.
   • Latency: Consistently tests near the top for out-of-the-box low latency (~500ms or lower depending on chosen providers).
2. Retell AI
   • Best For: Production-ready phone agents with visual workflows and quick deployment.
   • Why it shines: Retell AI abstracts away the painful telephony and WebRTC synchronization. It offers native features like batch calling, easy warm/cold phone transfers, and visual conversation state management.
   • Latency: Highly optimized for phone networks, though slightly more opinionated than Vapi regarding stack configuration.

Top Infrastructure Frameworks (Lowest Latency & Scale)

1. LiveKit (with LiveKit Agents)
   • Best For: Absolute lowest latency, self-hosting, and massive voice/video scale.
   • Why it shines: LiveKit is the real-time WebRTC backbone that many upper-tier voice platforms actually use under the hood. By building directly on LiveKit Agents, you get fine-grained control over audio codecs, server placement (global edge routing), and zero markup on per-minute provider costs.
   • Latency: Unbeatable if deployed close to your LLM/TTS endpoints, because you remove an entire middleman orchestration layer.
2. Pipecat
   • Best For: Open-source framework orchestration for voice pipelines.
   • Why it shines: Developed by Daily, Pipecat is an open-source framework specifically designed for building real-time voice and multimodal AI agents. It plugs directly into LiveKit, WebRTC, or SIP, giving you modular code control over frame-by-frame audio processing and interruption logic.

Quick Comparison to Help You Decide

• Choose Vapi if you want to write code, test different AI models rapidly, and launch a production phone agent in days without managing WebRTC servers.
• Choose Retell AI if you prefer a mix of developer APIs and smooth dashboard tools for call transferring, batch operations, and telephony handling.
• Choose LiveKit if you have engineering bandwidth, expect massive call volumes where per-minute API fees would eat your margins, or have strict data-privacy/self-hosting requirements.

To help narrow this down, tell me:

• Do you prefer a managed API (pay-per-minute, fast setup) or self-hosting/open-source (lower cost at scale)?
• What is your expected call volume?

Here are top web results for exploring this topic:

Ringly.io·https://www.ringly.io The best AI voice agent platforms in 2026: tested and compared best-ai-voice-agent-platform. In this article. Text LinkWhat are the best AI voice agent platforms in 2026?How we evaluated these platformsThe 7 best AI voice agent platformsAI voice agent platform co Arahi AI·https://arahi.ai**Best AI Voice Agents** 2026: 11 Platforms Ranked & Tested | Arahi AI Most platforms cluster between $0.07–$0.20 per minute before LLM costs. •Telephony integration (Twilio, Vonage, Plivo) is the hidden sorting criterion — not all platforms handle warm transfer, SIP tru Venture Harbour·https://ventureharbour.com**Voice AI Platforms** Compared: I Built Voice Agents on 7 Tools Hands-on review of 7 voice AI platforms — VAPI, Retell, Synthflow, Bland and more — tested for latency, cost-per-minute and build experience. Reddit·https://www.reddit.com**Best** solution for building a real-time voice -to-voice AI agent ... - Reddit If the goal is production-grade voice AI with minimal ops, I'd skip frameworks that are heavy on DIY setup. Agora's Conversational AI Engine checks every box you listed and is much easier to deploy th Retell AI·https://www.retellai.com**Best AI Phone Agents** : 8 Platforms Ranked & Tested 2026 | Retell AI 1. Retell AI: Best Overall for Production Phone Agents. What does it do? Builds, deploys, and monitors LLM-powered voice agents for inbound and outbound calls with no-code and full API control. Who is Inworld AI·https://inworld.ai**Best Voice Agent Platforms** (2026): 8 Tools Compared - Inworld AI A voice agent is software that listens to a user, reasons about what was said, and responds with spoken audio. The typical architecture chains together speech-to-text (STT), a large language model (LL www.vellum.ai·https://www.vellum.ai/blog/ai-voice-agent-platforms-guide Top 10 AI Voice Agent Platforms Guide (2026) - Vellum Retell AI : Best AI voice agent platform for teams that need real-time, low latency phone agents with transparent per-minute pricing and flexible telephony integrations. SquadStack AI : Best for teams LiveKit·https://livekit.com LiveKit: Build voice , video, and physical AI Its ease of use, feature-rich and flexible architecture, and production-ready infrastructure allowed us to deploy our voice agents with confidence. Walker Ward Principal Software Engineer, Podium. LFG Telnyx·https://telnyx.com**Best Voice AI** Orchestration Platforms (2026): 8 Options Reviewed We compare eight tools, from open-source frameworks to full-stack platforms, on what each owns, how it handles latency, and what it actually costs. Osman Husain Telnyx. By Osman Husain. voice ai orche www.bland.ai·https://www.bland.ai/Bland | Enterprise Voice AI Platform for Phone Agents Build, deploy, and monitor AI voice agents that sound human. Self-hosted models, sub-second latency, and enterprise compliance.

If low latency is the #1 requirement for a phone agent, my shortlist in 2026 is:

My pick: Retell for most teams

For a production phone agent where you want low latency without building the entire voice infrastructure yourself, I'd choose Retell. Independent 2026 comparisons consistently put it among the fastest managed platforms, with roughly 600–800 ms response latency in typical configurations and sub-500 ms possible with aggressive optimization.

It also handles the annoying phone-agent pieces—telephony/SIP, interruption/barge-in, turn-taking, call analytics, etc.—instead of making you assemble them yourself.

But if you're optimizing for absolute latency...

I'd build:

Phone/SIP → LiveKit Agents → realtime speech model → streaming TTS

LiveKit Agents gives you much more control over the media pipeline and lets you colocate components, tune turn detection, choose your STT/LLM/TTS, and potentially self-host. That extra control can matter enormously for P95/P99 latency.

The key insight is that the platform itself isn't necessarily the latency bottleneck. A phone agent's perceived response time is roughly:

caller stops → endpoint detection → STT → LLM first token → TTS first audio → carrier/network

You want every stage streaming and ideally running in parallel. Modern TTS can get first audio down to tens of milliseconds, so orchestration and turn detection increasingly dominate the experience.

What I'd choose by scenario

• "I need a great phone agent live this week" → Retell
• "I need the lowest possible latency and have strong engineers" → LiveKit
• "I want complete control and Python" → Pipecat
• "I want flexibility + easy development" → Vapi
• "I want a simple speech-to-speech architecture" → OpenAI Realtime

One important caveat: don't choose based on vendor-reported latency alone. Test the exact combination of phone carrier + geography + turn detector + model + TTS that you'll deploy. A platform that advertises 500 ms can feel worse than a 700 ms system if its P95/P99 tail latency or interruption handling is poor.

If you tell me (1) inbound vs outbound, (2) expected calls/minute, (3) whether you need SIP/Twilio, and (4) your preferred LLM, I can recommend the lowest-latency stack and architecture rather than just the platform.

Choosing the "best" platform for a low-latency voice AI phone agent depends on whether you prefer an all-in-one developer orchestration layer , a telephony-native infrastructure , or a no-code builder . Latency in voice AI is a game of millimeters—every network hop and third-party API call adds milliseconds to the time-to-first-audio (TTFA).

The top platforms are categorized below by their primary strengths:

• Retell AI (Best Overall for Production Phone Agents)
  • Strengths: Optimized specifically for real-time conversational phone calls with robust sub-second turn-taking and native PSTN/SIP connectivity.
  • Why it's great for low latency: It handles the complex state management of WebRTC, audio streaming, and interruptions smoothly, minimizing the conversational lag that ruins phone agent experiences.
• Vapi (Best for Developer Flexibility)
  • Strengths: A model-agnostic, developer-first orchestration API. It lets you plug and play any Speech-to-Text (STT), Large Language Model (LLM), and Text-to-Speech (TTS) provider (like Groq, Deepgram, and ElevenLabs).
  • Why it's great for low latency: Excellent SDKs and modular pipeline control allow you to route through ultra-fast inference providers (e.g., pairing Groq with Cartesia or Deepgram) to shave off crucial milliseconds.
• Telnyx Voice AI / SignalWire (Best for Infrastructure-Level Speed)
  • Strengths: Full-stack communication providers that own the underlying carrier network, phone numbers, and SIP trunking alongside native AI processing.
  • Why it's great for low latency: By eliminating intermediate network hops and running media servers, STT, and LLM streaming on the same localized network edge, they achieve some of the lowest raw round-trip latencies in the industry (sub-200ms to sub-500ms).
• ElevenLabs Conversational AI (Best for Voice Realism & Speed)
  • Strengths: Industry-leading speech synthesis combined with a dedicated conversational orchestration layer.
  • Why it's great for low latency: Their optimized streaming models (like Flash v2.5) deliver sub-100ms TTS generation, though you will typically need to pair it with a telephony carrier like Retell or Telnyx to handle the actual phone call routing.
• Synthflow AI (Best No-Code / Agency Option)
  • Strengths: A visual, drag-and-drop builder aimed at teams or agencies looking to deploy functional phone bots fast without heavy engineering.
  • Trade-off: While it offers fast setup and native CRM integrations, highly customized no-code platforms can sometimes introduce slightly higher latency or rigid interruption handling compared to pure developer APIs.

Summary Recommendation

• If you want the fastest out-of-the-box reliability for phone calls: Go with Retell AI.
• If you want total control over the stack to mix and match the absolute fastest frontier models and voice engines: Build on Vapi or Telnyx.

To help narrow down the ideal architecture, let me know:

• Are you planning to build this custom via API or do you prefer a visual/no-code builder?
• What is your expected call volume (inbound vs. outbound)?

If your top priority is natural, low-latency phone conversations, there isn't a single best platform—it depends on how much control you want versus how much infrastructure you want to manage.

Here's how I'd break it down:

Industry comparisons consistently identify Vapi, Retell, Telnyx, Twilio, and ElevenLabs as the leading options, though published latency numbers aren't directly comparable because vendors measure different parts of the call pipeline.

My recommendations by use case

For most startups

• Vapi
• Fast to prototype
• Supports OpenAI, Anthropic, Gemini, and other models
• Good function calling
• Strong community
• Easy SIP/Twilio integrations

If I had to build an MVP this week, Vapi would probably be my first choice.

---

For production customer support

• Retell AI

Retell is particularly strong in:

• interruption handling (barge-in)
• endpoint detection
• monitoring and analytics
• call debugging
• production reliability

Many teams find its conversational feel more polished than generic voice pipelines.

---

For absolute lowest latency

• Telnyx Voice AI

One reason latency suffers is that audio bounces between multiple vendors:

Phone → Twilio → STT → LLM → TTS → Twilio

Platforms that keep more of that path together can reduce delay. Telnyx has published measurements showing very low carrier-path latency, though these benchmarks aren't directly comparable with every competitor's methodology.

---

If you're already using Twilio Stay on Twilio and use:

• OpenAI Realtime
• ConversationRelay
• Streaming media
• Your own business logic

You'll write more code but retain maximum flexibility.

What actually determines latency

The platform matters, but these factors often matter even more:

• Streaming speech recognition (don't wait for complete sentences)
• Streaming text-to-speech
• Fast endpoint detection (around 200–300 ms)
• Running all services in the same cloud region
• Minimizing external API hops
• Fast function/tool execution
• A model optimized for real-time voice

A well-engineered system can often feel significantly faster than a platform with better marketing claims.

If I were building today

For a SaaS phone agent:

• Vapi + OpenAI Realtime + Twilio numbers

For an enterprise contact center:

• Retell AI

For the fastest possible infrastructure:

• Telnyx Voice AI

For a custom voice platform with an experienced engineering team:

• Twilio Media Streams + OpenAI Realtime + your own orchestration

A few questions would narrow the recommendation further:

• Are the calls inbound, outbound, or both?
• Will the agent need to book appointments, query CRMs, or transfer to humans?
• Approximately how many calls per day do you expect (tens, hundreds, or thousands)?

The "best" platform for a low-latency voice AI phone agent depends on whether you want a pre-optimized managed service or a WebRTC/infrastructure-level framework where you own every millisecond.

The leading platforms are categorized below by their architectural strengths and latency performance:

• Retell AI : Best overall for production phone agents. It hits an out-of-the-box latency of ~ 600ms through pre-optimized pipelines, handles natural interruptions seamlessly, and includes built-in telephony and compliance (SOC 2, HIPAA) without costly add-ons.
• Vapi : Best for modular flexibility. It is an API-first platform allowing you to freely mix and match STT (Speech-to-Text), LLM, and TTS (Text-to-Speech) providers. However, its latency can range higher (1,000ms - 1,500ms) depending on how many third-party API hops your chosen stack requires.
• LiveKit Agents : Best for real-time, WebRTC-native infrastructure. If you have DevOps resources and want to self-host or tightly control a multimodal, ultra-low latency media pipeline without relying on rigid third-party wrappers, LiveKit provides the underlying real-time audio routing infrastructure.
• Bland AI : Best for high-volume, enterprise outbound campaigns. It relies on a bundled, self-hosted infrastructure approach, making it great for bulk dialing and deterministic call pathways, though its conversational latency can occasionally lag behind Retell's optimized runtime.
• Synthflow AI : Best for rapid, no-code/low-code deployments. It offers a visual drag-and-drop builder for agencies and small-to-medium businesses, achieving decent sub-500ms performance at the expense of deep code-level customization.

To help narrow down the right choice, tell me:

• Are you planning to build inbound support, outbound sales , or an automated receptionist?
• Do you prefer a managed platform (like Retell/Vapi) or an open/infrastructure framework (like LiveKit)?
• What is your expected monthly call volume?

The “best” platform depends on whether you optimize for fast launch, lowest latency, or maximum control. For a production phone agent, I’d shortlist these:

My default recommendations

1. Building a startup MVP / first 10,000 calls → Retell or Vapi

• You get phone numbers, call handling, interruption (“barge-in”), streaming, tool calls, analytics, and debugging.
• You can ship in days instead of building a media pipeline.
• Retell tends to be more “batteries included”; Vapi tends to appeal more to engineers who want component flexibility.

2. Building a company-defining voice product → LiveKit Agents + your own model stack

Use this if you care about:

• custom turn-taking logic
• proprietary orchestration
• multiple agents
• deep observability
• avoiding vendor lock-in

The cost is engineering time: you become responsible for more of the real-time stack.

3. Maximum phone latency optimization → Control the whole path

Latency is usually dominated by:

1. telephony ingress/egress
2. voice activity detection
3. speech-to-text delay
4. LLM first-token latency
5. text-to-speech first audio

A “fast” LLM with a slow telephony path will still feel slow. Some comparisons show meaningful differences between carrier paths and platforms, but benchmarks vary heavily by configuration.

Stack I’d build today for a high-quality agent

Pragmatic production stack:

• Telephony: Telnyx or Twilio
• Agent runtime: Retell/Vapi initially, migrate to LiveKit if needed
• STT: Deepgram streaming
• LLM: OpenAI Realtime or a fast streaming LLM
• TTS: ElevenLabs / Cartesia / similar streaming voice provider
• Data: Postgres + vector DB for knowledge retrieval
• Observability: call transcripts + latency metrics per turn

The biggest mistake is optimizing model choice before optimizing the conversation loop. A mediocre model with excellent streaming, interruption handling, and prompt/tool design often feels more human than a smarter model with 2–3 seconds of dead air.

If I had to pick one today:

• Solo/small engineering team: Retell
• Developer-heavy startup: Vapi
• VC-backed company building a core voice platform: LiveKit
• Enterprise call center replacement: Twilio/Telnyx + custom stack