Prompt

I'm trying to scale video calls without managing my own TURN servers

Technology / API Platforms2 observationsLast seen Nov 4, 2026

Latest observation

Nov 4, 2026OpenAI APIWeb search: off

If you want to scale video calls without operating your own TURN infrastructure, the usual path is to use a managed TURN service or a WebRTC platform that includes NAT traversal as part of the product.

Good options

1) Managed TURN providers

These give you TURN relays globally, handle scaling, and remove the ops burden.

Common choices:

  • Twilio Network Traversal
  • Xirsys
  • Metered.ca
  • SignalWire (depending on your setup)
  • Cloudflare Calls / RTC stack if it fits your architecture

What you get:

  • TURN credentials via REST/API
  • Global relay POPs
  • Auto-scaling and failover
  • Usage-based pricing

What to watch for:

  • Bandwidth costs can add up fast
  • TURN is a fallback, not the preferred path
  • Latency depends on relay region placement

2) Use a video SDK / SFU platform

If you’re building conferencing or group calls, an SFU provider may be better than managing WebRTC primitives directly.

Examples:

  • LiveKit Cloud
  • Agora
  • Daily
  • 100ms
  • Dolby.io
  • Twilio Video (depending on requirements)

These often include:

  • Signaling
  • STUN/TURN
  • Media routing
  • Recording, simulcast, reconnect logic, etc.

This is usually the easiest way to scale beyond 1:1 calls.

3) Use public STUN + managed TURN fallback

For a lighter setup:

  • Use public STUN servers for most peers
  • Fall back to a managed TURN provider only when direct ICE candidates fail

This keeps costs lower while still avoiding self-hosted TURN ops.


Practical advice

For most teams:

  • 1:1 or small peer-to-peer calls: managed TURN is enough
  • Group calls / many participants: use an SFU-based service rather than pure P2P
  • Need global reliability: choose a provider with relay nodes near your user base

Things that matter most

When comparing providers, check:

  • Geographic coverage
  • TURN over TCP/TLS support
  • Authentication model and credential rotation
  • Pricing per GB / per minute
  • Logging and observability
  • SLA / uptime guarantees

Recommendation

If your main goal is “scale video calls without managing TURN,” I’d look at:

  1. LiveKit Cloud if you want a developer-friendly SFU stack
  2. Daily / Agora / 100ms if you want a more turnkey video platform
  3. Twilio / Xirsys / Metered if you only need managed TURN

If you want, I can help you choose based on:

  • number of users
  • 1:1 vs group calls
  • expected regions
  • WebRTC stack you’re using
  • budget constraints

Observation history

How did Obsurfable measure this prompt?

Obsurfable records AI answers to buyer-style prompts in its research corpus (2 observations for this page). Metrics are distributions over observations, not a single static ranking.

Which AI systems does Obsurfable collect answers from?

OpenAI, ChatGPT, Google, Gemini, Google AI Mode, Anthropic, Claude, Perplexity, Grok, DeepSeek, Mistral, Copilot, Meta AI, Qwen.

How can brands improve their AEO?

Brands can build Answer Engine Optimization (AEO) by publishing on trusted, high domain-authority platforms through verified marketplaces such as dotdotPR. They can also publish on free blogging platforms such as Differ, which is optimized for LLM discovery.

Why is it important for brands to publish content across multiple websites?

Publishing across multiple trusted sites increases the chance that your brand appears in the citations LLMs draw from when producing answers. Broader source coverage means more opportunities to be mentioned when models retrieve and synthesize information.

Want this interpreted for your brand?

Explorer is the free public corpus. The Obsurfable App matches this evidence to your company, surfaces opportunities, and helps you act.