EdgeMatrix’s
Mission
Accelerating the development &
porting of Deep Learning models on Edge devices. We do this by
providing a enterprise ready,
low-code end-to-end platform to
manage the entire Edge AI lifecycle.
EdgeMatrix’s
Much Realized Benefits
Unprecedented Performance
Run models on CPUs at GPU speeds. No special hardware required.
Reduce Costs
Deploy and scale models on commodity CPU servers from the cloud to the edge.
Smaller Footprint
Unlock edge possibilities by reducing model footprint by 10-20x.
Run EdgeMatrix.io Anywhere
Deploy the platform with flexibility - on premise, or in the cloud.
Bridging the Gap [AI onto Edge] Much Faster & Economical Edge AI Platform
If you are aiming at federating AI or complex Deep Learning models on to any low-cost edge devices or looking at porting your existing models on to any target hardware (and yet aiming to retain the accuracy), EdgeMatrix.io is your solution.
We have done all the heavy lifting for you so that we can provide a seamless, easy, and fast end-to end Edge AI platform so you can deploy Neural Net models onto countless devices.
We have done all the heavy lifting for you so that we can provide a seamless, easy, and fast end-to end Edge AI platform so you can deploy Neural Net models onto countless devices.
The First Enterprise Ready Edge AI Platform
EdgeMatrix platform actively takes care of production constraints in the porting process, such as optimizing the model for the target inference hardware, to dramatically increase your success rate in production.
End to End
Inference Acceleration
EdgeMatrix.io provides you with unmatched end-to-end accuracy-preserving inference acceleration for your neural net models on the Edge, IoT Devices, & FPGAs.
Accelerated by Revolutionary Technology
AI
Made by
AI
EdgeMatrix platform is powered by SL’s proprietary algorithmic optimization engine that squeezes the most out of any hardware.
This engine revises a given trained model to optimally speed up its runtime, while preserving the model’s baseline accuracy.
Simple, Intuitive, And Efficient.
EdgeMatrix prune and quantize your deep learning models to minimize footprint & run on CPUs at GPU speeds.
Industry Standard Frameworks
EdgeMatrix prune and quantize your deep learning models to minimize footprint & run on CPUs at GPU speeds.
Does your hardware lacks Deep Learning Accelerator?
Ready-to-use Deep Learning Hardware Accelerator to bring AI abilities onto your Low Cost hardware
Low Power & Energy Optimized
High Flexibility & Scalability
Faster & Economical
High Throughput
Low Latency
Secure Your Connected operations with EdgeMatrix.io
Orchestrate your connected operations securely and at scale with choice of hardware, datasets, and models so you can focus operational simplicity at a highly affordable Total Cost of Ownership (TCO).
Why Edge AI developers love us?
Accelerate Inference on Edge
Get 3x-15x speedup optimization for inference throughput/latency while maintaining accuracy, enabling new use cases on your hardware of choice
Reach Production Faster
Shorten development cycle from months to weeks with automated tools. No more endless iterations and dozens of different libraries.
Maximize Your Hardware Potential
Scale up with existing hardware. No need for infrastructure changes and extra costs. Gain up to 80% reduction in compute costs.
Explore your business options.
CAPEX to OPEX
Pay As you Grow
Flexible Subscription Models
Unleash Edge AI Potential
Discover what ExgeMatix.io can offer for your Enterprise.
Accurate, Seamless, Fast, Economical – serving what is required at most! Interested to know more?
Case studies & stories
We work together across the globe to make a world of difference.
SandLogic’s CORE now supports Intel’s OpenVINO
SandLogic’s CORE (Code_Once_Run_Everywhere) tool now includes support for Intel’s OpenVINO for Intel’s x86 processors. CORE tool can now convert their favourite neural nets from any framework (TF 1.x, TF2.x, PyTorch, ONNX, TFLite) and optimize the neural net for any x86 device of the user’s choice.
Enabling Deep Learning and Computer Vision capabilities on the Shakti Vajra SoC
Making a non-AI enabled hardware, AI capable using EdgeMatrix.io. Porting and Integration of open-source IP modules for Neural Processing Engine (NPE), MIPI-CSI2 camera interface with Shakti Vajra SoC. Also, Porting and Patching Linux OS and Device Drivers on the updated SoC.
Porting of Detection & Classification model to QCS 605
Our developers utilising EdgeMatrix platform for Developing & Porting AI framework for their upcoming Camera line (Dashcam & Cabin Monitoring Cam) based on SNPE DLC
Created missing Operators
Using EdgeMatrix proprietary tech stack, developers ported multiple models, served those models on Triton Server and did multiplexing to support inference on Multiple Camera inputs.
Architecture re-design to accommodate on Edge (QCS 603)
A multi-model distress recognition system for passenger transportation industry was ported to QCS 603 based device, Multi-model Pyramid Architecture.
Porting & Optimization of Custom Object Detection Models to Edge
The end product houses an Industrial grade camera, Jetson Nano / Xilinx board, Custom lighting equipment enclosed in a IP67 certified housing. Models are ported on to Jetson / Xilinx boards to provide edge-based intelligence.