01
Deploy at the edge
We are industrializing the Blackwell architecture for telecom environments. Stations near users—at carrier POPs or tower-adjacent sites—so inference happens locally.
Edge inference for voice, vision, and LLMs
AI CDN - Run AI closer to your users at telecom scale.
SwiftInference deploys multi-tenant edge stations at carrier and tower sites to cut latency, reduce bandwidth, and deliver predictable inference economics.
Guaranteed slots + spot capacity
Streaming-first (voice & video)
Secure updates
Metrics
latency
3 x faster
Fastest Node
Bandwidth saved
45%
Fast Inference
Uptime target
99.9%
How SwiftInference works
Drop-in edge inference that behaves like cloud: auth, routing, quotas, SLAs, and observability.
02
Pin models & enforce slots
Two reserved slots provide predictable performance. A third optional spot slot absorbs bursty workloads.
03
Route intelligently
SwiftFabric routes each request to the best node based on health, load, latency, and policy—then streams results.
04
Operate safely
Secure boot, attestation, signed updates, and per-tenant isolation guard workloads and infrastructure.
Designed for real-time
Real-time AI inference for LLM workloads, voice and video with predictable latency.
Use cases
🧠
LLM inference & RAG
Serve token streams closer to users. Run embeddings on spot capacity and keep the main model pinned.
Slot A
Pinned weights
🗣️
Real-time voice AI
Low-latency STT/TTS and conversational agents near users. Protects jitter and improves turn-taking.
Slot A/B
Streaming
👁️
Computer vision at the edge
Reduce backhaul by processing video locally: object detection, safety, retail analytics, and industrial monitoring.
Slot B/C
Bandwidth saver
Built to integrate with
vLLM
Triton
TensorRT-LLM
Kubernetes*
Envoy
White papers
📡
For Telcos
Monetize tower and POP real estate with reserved + spot inference capacity, SLA reporting, and data-sovereignty deals.
Revenue
MEC / Private 5G
🧠
For AI companies
Own your inference like a CDN: distributed edge POPs, predictable cost, tighter p99, and enterprise-friendly data locality.
Inference CDN
Lower OPEX
🧩
For app developers
SDK/API edge inference: near-device latency without shipping huge models, with streaming output and predictable plans.
SDK
Streaming
Pricing
Spot
Best-effort capacity
$999/mo
- On demand workloads
- Contended
Most popular
Guaranteed
Secondary slot
$2,999/mo
- Guaranteed throughput
- Priority scheduling
- Latency SLO reporting
Anchor
Primary slot + enterprise
$3,999/mo
- Highest priority
- Custom routing + SLAs
- Dedicated support
Pricing shown is illustrative for early deployments. Final pricing depends on site density, workload characteristics, and SLA terms.
FAQ
Answers to the questions buyers frequently ask.
How many customers can share a single node?
Two customers get guaranteed slots. A third optional spot slot is interruptible. We don’t oversell beyond that because tail latency matters.
Is SwiftInference a hardware company?
No. We focus on the platform: routing, slot enforcement, observability, and secure operations. We deploy on best-fit edge systems for the site class.
How do you protect customer IP and models?
Secure boot, signed updates, and node attestation are required before workloads run. Models can be encrypted at rest with keys released only to trusted nodes.
What’s the fastest way to pilot?
Pick one metro area and 20–50 edge sites (carrier POPs or tower-adjacent). We deploy, integrate your runtime, and tune for your p95/p99 targets.
Request a pilot
Tell us your workload (voice, vision, LLM), target metros, and SLA requirements. We’ll respond with a deployment plan, slot sizing, and pricing.
Email
hello@swiftinference.ai
Partnerships
partners@swiftinference.ai