PolarGrid

Real-Time AI Inference At The Edge.

[PolarGrid @PolarGrid]

Most multi-colo inference stacks add a central brain for routing and deployment, and it becomes the bottleneck

We run each edge node independently. The router makes one decision, then the client connects directly to the right GPU for low-latency inference
https://t.co/lStPlKl25Q

[PolarGrid @PolarGrid]

Most inference platforms make the same mistake: every request hits a central gateway before reaching a GPU, adding 50–200ms before inference begins

At @PolarGrid, the routing decision happens once, leading to low-latency inference delivered from the edge

https://t.co/k5JWTmZdz7

[PolarGrid @PolarGrid]

There’s a one-second rule in conversation. Cross it, and people disengage. Voice AI is no different.

We’re at 364ms p50 end-to-end (audio in → audio out, real RTT) on Ada. Here’s what it takes to build a sub-400ms STT → LLM → TTS pipeline.
https://t.co/HEQvE7XuF1

[PolarGrid @PolarGrid]

Voice agents don’t fail on accuracy; they fail on timing.

That half-second pause gets them shelved.

We've spent the past year optimizing milliseconds because voice agents that don't match human conversational timing don't get used.

Read the article👇
https://t.co/0yATMm7G3l

[PolarGrid @PolarGrid]

Most inference still runs in centralized clouds, so requests travel hundreds/thousands of km and back. That round-trip breaks real-time apps.

@PolarGrid is building a distributed edge-GPU platform so developers can run models near users.

Check it out! 👇
https://t.co/z0X95wujOU

[Tech Investing News @INN_Technology]

.@PolarGrid, a Canadian startup, is shifting #AI inference to the edge to reduce latency and improve real-time responsiveness, challenging centralized data centers. #ArtificialIntelligenceInvesting https://t.co/1qc1ROkRPa

[PolarGrid @PolarGrid]

Our Co-Founder and VP of Engineering, Sev Geraskin, will be leading a workshop at @UBC today to share @PolarGrid journey, and how we use AI to ship products faster without compromising quality!

[PolarGrid @PolarGrid]

Proud to see PolarGrid featured in @DigMedia.

We’re building what’s missing from the AI stack: an inference network designed for real-time, not batch.

Read the article below! 👇 https://t.co/Bz8VPLoONY

[BetaKit @BetaKit]

.@PolarGrid CEO Rade Kovacevic say GenAI video and voice will be killer apps once they can function in real-time. But what other new experiences might emerge once AI can move in milliseconds around the world?

🎧 Listen to Rade on The BetaKit Podcast:

https://t.co/4gDj6oyAec

[PolarGrid @PolarGrid]

We shipped our first production management console in just over a week. No design team needed.

Here's our pipeline that replaced the months of work on our front end. 👇
https://t.co/t8oFTra23F

[PolarGrid @PolarGrid]

AI has a latency problem.

Recently on the @BetaKit podcast, our CEO @rade_NK explains why centralized cloud inference can’t power real-time AI. PolarGrid’s edge GPU network cuts network latency 70%+ to enable sub-30ms inference, without multi-zone complexity.

Check it out!👇

[Rade @Rade_NK]

When we cut inference network latency, entire categories of real-time AI applications suddenly become viable. Thanks to @BetaKit for pushing the convo.

https://t.co/8cfua0yKQY