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New! Ultra Efficient SLMs!

Develop and Optimize AI
for any Edge Device

On-premise and Cloud Solutions for Edge AI Developers

Trusted by industry leaders and research partners

Our features for developing
efficient on-device AI

Tools that fits any team size and skill level

ON-PREM
SaaS

Embedl Hub

Secure MLOps platform for compliant edge AI workflows.

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On-prem or SaaS

Integrated edge AI collaboration solutions behind one interface

Actionable errors and debugging

Compare model graphs, on-device latency, layer-wise PSNR, and memory use

Cloud & on-prem device farms

Run models on on-demand hardware from multiple vendors, no device setup

Enterprise integrations

Integrates with safety & verification systems to enable compliant workflows

LLM
VLM
VLA

Embedl Models

Popular models made compatible and highly optimized for specific edge hardware.

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Deployment-ready packages

Full code, kernels and recipes to run models optimally on specific devices

Find the best model

Quickly try out different models for your use case before fine-tuning and licencing

Save time, cost and power

Reduce time to market, unit costs and power consumption using pre-optimized and device compatible models

GenAI focus

Supplying the latest generative models for tomorrow's edge AI products

VISUALIZATION
PROFILING

Embedl Studio

Standalone Edge AI model visualizer and profiling app.

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Graph & problem analysis

Visualize and understand the changes compilation introduces in each step

Performance analysis

Compare on-device latency, quantization precision, operation type breakdown

Compare model versions

Easily see how different quantization and compiler settings affect the graph

One tool to rule them all

Integrated tool for visualizing multi-step compilation and benchmark data

CLI
LIBRARY

Embedl Next

Edge AI conversion, compilation and quantization to easily get models running on hardware.

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Simple setup and workflow

Simple setup and workflow to get started with compilation and quantization for various devices and toolchains

Hardware-aware

Build models with hardware-aware operations with fusion behavior and compiler constraints enforced directly in PyTorch

Quantization

Explicitly quantization in PyTorch ensures consistent behavior after compilation with advanced mixed precision

Faster time-to-market

Design compatibility and edge performance into the model already from the start of development

Discover our
benchmark results

A selection of our optimization results across different model and hardware targets.

Target domains for scalable Edge AI deployments

Enabling embedded intelligence for any use case

Car
AUTOMOTIVE
Drone
DEFENSE
Robot
ROBOTICS
Robot
INDUSTRIAL AUTOMATION
IoT
INTERNET OF THINGS
Computer and a mobile phone
PC AND MOBILE

Awards

1-Oct-26-2025-07-52-27-8571-PM

Outstanding innovation honored by the Swedish Royal Academy.

NyT 33 List

One of Sweden's 33 most promising tech startups.

HiPeac

Excellence in high-performance and embedded computing.

TECHARENA

Top 100 Startups in the Tech Arena Startup & Scaleup competition.

I4MS

European leader driving industrial digital transformation

CBS Insights

Global ranking of the top 100 most promising private AI startups worldwide.

Compiled notes from the team

Stay updated on Embedl’s latest insights and industry events.

Get started with Embedl

Start developing and optimizing your edge AI models.