Robotics · Live streaming · Voice AI · Inference · Netcode

Real-time infrastructure for physical and multimodal AI.

One QUIC transport and one C++ runtime carry robot control, live video, phone calls and model output on a single connection.

Measured, not modelled

One runtime. Real hardware. Real numbers.

Robot teleoperation63live sessions on one CPU core, at 40 ms p95 round trip and 100% deliveryMeasured · relay on GCE c4-highcpu-8, real NIC, run to saturation
Voice24,000concurrent calls on one 8-vCPU server, every packet delivered, at 52% CPUMeasured · G.711, same box and harness: pion 22,000 at 83% CPU · Asterisk 4,000 · FreeSWITCH 1,000
Live streaming1,500live 1080p viewers on one 8-vCPU server, full bitrate, 0 lostMeasured · RTMP ingest → relay on GCE c4-highcpu-8 → SDK viewers, 9 Gbps out at 61% CPU
Inference2.7×faster follow-up turn with our KV cache, identical outputMeasured · RTX A5000, vLLM, Qwen2.5-1.5B, 7.2k-token prompt: 129 ms vs 353 ms

Every figure comes from a benchmark we can rerun in front of you.

Running today
Contact centre · MalaysiaA live contact centre runs on our runtime, on-prem, through a white-label partner.In production
Voice-AI platform · IndiaReal inbound phone calls reach its AI agents through our Mumbai SIP edge.Pilot
Voice-agent companyIts own voice agent is being integrated on our transport.Integration under test
one box · 8 cores
voiceinferencewebrtcsiproboticsgames
01 · The substrate

It starts with one packet.

A single unit of your data, on the wire.

One live connection.

That packet is one of thousands on a single connection.

One core.

Every core runs its own connections, full tilt.

122,367★

messages/second on one 8-core box — and improving. 36,732 concurrent connections at 0.4% CPU.

One substrate.

Every box, every modality, on the same transport.

AI
TV
noise
caller
coworker
02 · Voice AI

It starts with one sample.

A scrap of sound, captured the instant it's spoken.

Which becomes speech.

Words on the wire, in real time.

A live call.

Caller, model, agent — one pipe, both directions.

It hears the whole room.

The line tells the caller from the TV, a coworker, or background noise — and listens to the right one.

Thousands of calls at once.

On every provider, with first-class barge-in.

OpenAI RealtimeGemini LiveElevenLabsAnthropicDeepgram
Explore in detail →
03 · Interactive live

It starts with one camera.

A teacher, a seller, a match: RTMP or WHIP in.

Frames, the moment they exist.

Media-over-QUIC sends each frame as soon as it is made, not in 6-second chunks.

One relay, every viewer.

Fan-out at the edge, with a fallback to HLS on Safari.

1,500

live 1080p viewers on one 8-vCPU server, nothing lost.

RTMPWHIPMoQHLS fallback
Explore in detail →
04 · Inference

It starts with one token.

A single piece of the answer, fresh off the model.

A stream off the GPU.

Tokens leave the GPU and start arriving immediately.

Straight to your client.

Point your OpenAI-compatible client at the line — nothing in your app changes.

First token, fast.

Same SSE wire your client already speaks — the moment a token exists, your app has it.

Explore in detail →
meet.example.com/abc-xyz
you
alex
jordan
sam
05 · Browser · WebRTC

Audio, video, text and control.

Four modalities, in one place.

Each on its own lane.

A stall in one never blocks another — no head-of-line blocking.

All on one connection.

One line, nothing to glue together.

On your transport.

Your path end to end — no plugins, no native app.

Explore in detail →
06 · SIP · Telephony

It starts with one call.

A carrier hands you an inbound call.

Then straight to your agent.

Media rides QUIC direct to the agent — no extra hops in the path.

Pull a human onto the line.

Listen, whisper, or take over — over the same connection, without rerouting the call.

One call, the whole wallboard.

Fan it out to every supervisor and dashboard, live.

TwilioPlivoVobizTeleCMITata IMSAudiocodes
Explore in detail →
07 · Robotics

One robot, in control.

Onboard autonomy stays on its own network.

Its data, in realtime.

A live mirror of everything it senses.

Up to the cloud.

Reaches the cloud over QUIC — observe from anywhere.

500

live tracks per shard at 50 fps, zero loss.

ROS 2ZenohMQTTDDS
Explore in detail →
08 · Games · Netcode

A player acts.

Input rides its own fast lane, as datagrams.

Two lanes, one session.

Fast state as datagrams, chat and events on reliable streams.

Even behind a firewall.

Players whose network blocks game ports still connect, on port 443.

Every player, in sync.

Tick-aligned state, lobby and matchmaking included.

UnityWeb · WebTransport
Explore in detail →
Seven workloads converge on one substratevoicestreaminginferencewebrtcsiproboticsgames
09 · One substrate

Seven workloads. One substrate.

Every branch flows back into the same transport line.

7

workloads, one transport. Add a workload, not a stack.

Inference

Serving that respects the GPU.

Inference runs on the same connection as your audio, video and robot control, so the model knows the moment its answer stops mattering.

Cancel propagation

The GPU stops when the user does.

A caller hangs up, a deadline passes, or the user talks over the agent. The transport carries that signal to the model and the generation stops. You stop paying for tokens nobody will hear.

Three triggers · caller · deadline · newer turn
ClutchKV

Our own KV cache for vLLM.

Written in C++. It saves the attention state of a conversation and loads it back on the next turn, so the model does not compute the same prompt twice.

Follow-up turn 129 ms vs 353 ms recompute · 2.7× · identical tokens
Vision for robots

Faster answers about the scene.

The same cache works for vision-language models. A robot that asks several questions about one task gets its first answer about twice as fast.

Qwen2.5-VL-3B · first token 144 ms → 69 ms with a shared task prompt
KV-aware routing

Each request goes to the right GPU.

The router reads live cache and load metrics from Triton and TensorRT-LLM, and picks a GPU on that data. OpenAI-compatible API, your model, your GPUs.

Least-cache and least-busy strategies across pooled GPUs
Proof products

Utilities that prove the runtime.

We built our own VPN, remote desktop and tunnel on the same transport that carries robots, video and voice. We run them every day, so the runtime is tested by long, ordinary use, not only by benchmarks. You can use them too.

VPN

A VPN that keeps latency flat under load.

IP over QUIC. Sessions survive a change of network, and traffic on port 443 looks like ordinary HTTPS. Two-factor sign-in and per-user entitlements. Desktop clients for Windows, macOS and Linux.

Measured vs Quincy · RTT under load 0.51 ms vs 14.69 ms · 38% less CPU per GB at 4 cores
QuickDesk

Remote desktop on your own relay.

Screens go through a relay you host, so pixels never leave your infrastructure. Frames carry priority and expiry, and sessions survive roaming. Attended or unattended.

Windows · macOS · Linux · Android
Tunnel

Public endpoints for private services.

A self-hosted alternative to ngrok and frp. One command gives a local service with no public IP a stable public URL, with token and IP policy at the edge instead of in your app.

HTTP · TCP · UDP · self-host or cloud
Drop-in SDKs

Ship on the substrate in an afternoon.

Nine language SDKs, from the browser to embedded devices, plus a ROS 2 middleware binding for robots.

py

Python

Async client, drop-in for the realtime API. Packages are shared during your pilot.

ts

TypeScript

Browser + Node, with a helper for browser media over your transport.

++

C++ / Rust

Bare-metal bindings to the core. Zero-copy frame handoff.

# realtime voice in 6 lines
from telequick import Session
s = Session(provider="openai-realtime")
async for ev in s.connect("+1..."):
    if ev.bargein: s.cancel()   # instant
    play(ev.audio)

Coming from another transport? The migration guide maps your existing calls onto the substrate one site at a time.

Read the migration guide →
Pricing

Start with a paid pilot.

Six weeks on your real traffic, with success criteria we agree in writing. The pilot fee is credited to your first month if you continue.

Production is priced per concurrent channel per month, with telephony passed through. On-prem is licensed per node. We quote against your workload after a 30-minute call.

FAQ

Questions builders ask.

Teams whose product breaks when the network is slow: voice-AI agents on phone lines, interactive live video (classes, live commerce, watch-alongs), robot teleoperation, and model serving that streams to users. All of them run on the same QUIC transport and the same C++ runtime. Each use case has its own page with its own numbers and questions; start with the one closest to your product.

No. The substrate speaks the interfaces you already use: a drop-in shim for OpenAI Realtime and a SIP listener for voice, RTMP and WHIP ingest for live video, a ROS 2 middleware binding for robots, and an OpenAI-compatible SSE endpoint for inference. Idiomatic SDKs in 9 languages are there when you want native types.

TCP delivers bytes in order, so one lost packet stalls everything behind it on the connection: your agent's audio waits behind a text message, a video frame waits behind a control command. QUIC streams are independent, so a lost packet delays only its own stream. QUIC also survives a change of network (Wi-Fi to mobile) without a new handshake. For background, read Chrome's announcement of HTTP/3 and IETF QUIC.

WebTransport ships in Chrome and Edge today. Safari and Firefox still trail, and some corporate proxies block UDP. Every client has a fallback: voice falls back to WebSocket over HTTPS with the same agent and the same interruption path, and the live-video player falls back to HLS, then MP4. You lose QUIC's benefits on that one client, and nothing else changes.

Every engagement starts with a paid 6-week pilot on your real traffic, with success criteria we agree in writing. The pilot fee is credited to your first month if you continue. Production is priced per concurrent channel per month for voice, with telephony passed through, and against delivered viewer-minutes for live video. On-prem is licensed per node. We quote against your workload after a 30-minute call.

Yes. The core is a single statically-linked binary plus a Redis. It runs in your own racks, including air-gapped sites where the model worker is also local. Hosted and self-hosted tenants run the same wire protocol, so behaviour matches.

Python, TypeScript, Go, Rust, Java, C#, Swift, Kotlin, and C++, with the same API shape and idiomatic types per language. They all wrap one C++ core via FFI, so a wire-protocol fix in the core ships to every SDK on rebuild. Python and TypeScript see the most use; the others run against a polyglot smoke matrix on every release.

We do not hold SOC 2 or HIPAA certification today. For regulated buyers we deploy on-prem, in your own data centre or cloud account, so audio, video and robot data stay inside your infrastructure. Hosted pilots run in a single region we agree with you. We do not train models on customer data.

It starts with a 30-minute call to map your current stack and agree the success criteria. We then connect your carrier, encoder, robot or model, and run the 6-week pilot on real traffic. Setup time depends on your integration; we give you a date on the first call.

Company

A deep-tech company, built in Mangaluru, Karnataka.

Telequick is built by Throughgen Innovations Private Limited. We write the runtime, the transport and the GPU cache ourselves, in C++, at the systems level. It is not a wrapper around someone else's API.

New to QUIC? Our free academy teaches networking from the ground up: layers, DNS, NAT, latency, then TCP versus QUIC and Media-over-QUIC, with hands-on labs.

Co-founderAshwin Kallaje

Designed and wrote the C++ runtime, the transport and the edge network. Leads the company and works directly with every pilot customer.

Co-founderSwasthik Padma

Leads go-to-market and product strategy. An interdisciplinary researcher, with a minor planet named after him.