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AI Video Encoding

Fewer bits, same quality.

AI preprocessing combined with in-house ASIC encoding logic delivers matched quality at lower bitrates, plus the low latency live delivery requires.

LEMONFLEX // AI×ASIC ENCODE PIPELINE
2026 · REV. 1
SDI / IP
SOURCE
RAW VIDEO
MODEL
AI PREPROCESS
ROI · DENOISE · DETAIL
U250
ASIC ENCODE
H.264 · HEVC · AV1
EDGE
DELIVERY
HLS · DASH · CMAF
Highlights

AI Video Encoding at a glance

AI preprocessing

Frame analysis directs bits toward visually significant regions.

ASIC encoding

The U250 encoding ASIC keeps latency below GPU pipelines.

Standard codecs

H.264, HEVC, and AV1 integrate with existing workflows as-is.

Low latency

Sub-frame latency, as live delivery requires.

Performance

Production-scale performance

Bitrate savings at matched quality (VMAF), plus encoding latency.

Bitrate savings (matched VMAF)
1080p−38%
4K−44%
8K−50%
Encoding latency
p506ms
p907ms
p998ms
Architecture

How it works

Preprocessing through encoding on one card, scaling per channel.

Real-time encoding

A low-latency encoder that runs inline in the live pipeline.

Unified acceleration

AI preprocessing and ASIC encoding execute on the same card.

Multi-channel scaling

Multi-channel 4K per card; add cards for 8K and heavy traffic.

Compare

Against the conventional approach

The same outcome, at a different cost.

Lemonflex AI × ASIC
GPU / software encoding
Bitrate (matched quality)
−30~50%
Baseline
Latency
Sub-frame
Tens of ms and up
Concurrent 4K channels / card
Up to 32ch
A handful
Power efficiency
ASIC efficiency
High GPU draw
Codecs
H.264·HEVC·AV1
Varies by codec
Scenarios

Where it applies

The approach differs depending on whether bitrate or latency is the bottleneck.

01
OTT · VOD

Re-encoding a catalog to cut delivery cost

Challenge

As the catalog grows, storage and CDN egress costs accumulate — but lowering bitrate raises quality complaints.

Approach

AI preprocessing concentrates bits on visually significant regions, then the catalog is re-encoded with a profile that holds VMAF while lowering bitrate.

Outcome
  • +30–50% lower bitrate at matched quality
  • +Storage and CDN egress fall together
  • +Standard codec output means no player changes
02
Live channel operations

Adding channels without adding servers

Challenge

Every new channel means another encoding server, which also means more rack space, power, and operational staff.

Approach

Move to a configuration where one card handles multi-channel 4K concurrently, absorbing channel growth through card additions instead.

Outcome
  • +Fewer servers for the same channel count
  • +Rack space and power budget reduced
  • +Per-channel failover maintains stability
03
Interactive & XR

Workloads where latency defines the experience

Challenge

Cloud gaming, teleoperation, and XR degrade noticeably at even tens of milliseconds of delay — a target software encoders struggle to hit.

Approach

The ASIC encoding path secures sub-frame latency, and keeping preprocessing on the same card removes the PCIe round trip.

Outcome
  • +Sub-frame latency through the encoding stage
  • +Latency distribution (p99) stays predictable
  • +Higher quality within the same latency budget
Spec

Key specifications

Bitrate
−30~50%
Codecs
H.264·HEVC·AV1
Latency
Sub-frame
Throughput
32ch 4K
Technical Specification

Technical specifications

Codec, throughput, and operational specifications.

Codecs & output
Video codecs
H.264 · HEVC · AV1
Bit depth
8 / 10-bit
Rate control
CBR · VBR · CRF · Capped VBR
GOP
Fixed · Adaptive · Scene-cut detection
ABR renditions
Up to 6 concurrent
Throughput & latency
Concurrent 4K channels
Up to 32ch / card
Maximum resolution
8K (multi-card)
Encoding latency
p50 6ms · p99 8ms
Bitrate savings
30–50% at matched VMAF
Operation
Mode
Live · Batch
Metadata
SCTE-35 · CEA-608/708 passthrough
Quality reporting
Per-channel VMAF and bitrate logs
Control
REST · gRPC API
Redundancy
Per-channel failover
FAQ

Frequently asked questions

Anything not covered here, we answer in a technical meeting.

What conditions produce the 30–50% bitrate savings?

It compares the bitrate required to hold identical VMAF against a software encoder. The margin varies with content complexity: it is largest on low-motion, noisy content and smallest on already-optimized high-quality sources. We provide measurements on your actual content during PoC.

How can bitrate drop without quality dropping?

AI preprocessing analyzes each frame and separates what viewers perceive from what they do not. Elements that consume bits without contributing to perceived quality — noise being the obvious one — are cleaned up before encoding, and the remaining bits go where they matter. The result is the same perceptual quality expressed in fewer bits.

When should AV1 be used?

AV1 has the highest compression efficiency, so the delivery cost savings are largest. You do need to check playback device coverage. A common setup emits AV1 for modern devices alongside H.264 for legacy compatibility.

Can we compare quality against our current encoder directly?

Yes. During PoC we feed identical source into both in parallel and measure VMAF, bitrate, and latency together. We agree on the deciding metrics before starting.

How is latency distribution (p99) managed?

The ASIC path is a fixed-function pipeline, so per-frame processing time varies little. Without the scheduling jitter or garbage collection pauses software encoders experience, the gap between p50 and p99 stays narrow.

Your video infrastructure,
one level up.

Start with a single card and scale as needed. We design the demo, the rollout, and the technical review with you.

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