A New Approach to Delivering On-Device Intelligence
We secure cyber-physical systems from outside influences by deploying AIoT, reducing cloud dependency and cutting costs with minimal latency.
What does OctaiPipe do?
Train, Fine Tune, and Manage Federated AI for IoT
OctaiPipe enables critical infrastructure data teams to confidently build and orchestrate networks of intelligent devices. We automate the use of privacy-enhancing distributed learning, fortifying security, and enhancing the performance of your Edge AI systems.
FL-Ops for IoT
Access production-grade federated learning that enhances on-device data privacy and security while minimising network and cloud costs.
Web UI
Monitor and manage your AI solutions deployed to edge devices with ease.
Python Library
Accelerate development with our comprehensive tools and templates designed to simplify and automate your builds.
Jupyter Notebook
Utilise your favorite IDE, complete with pre-built examples, documentation, and templates for seamless integration.
OctaiPipe Removes Risk and Cost Barriers to AIoT at Scale
Rather than move data, we move models to the data - train models locally at nodes, then aggregate the models
Maximises privacy and security
Minimises data transfer and compute costs
Relies less on network or cloud connectivity
Immutable properties of dockerised pipelines ensure replicability and portability between devices and locations
Why OctaiPipe?
Improve model
performance
performance
by x2
Reduce network
communication overheads
communication overheads
by x50
Cut training
costs
costs
by x100
OctaiPipe Enables You to Finally Unlock the Value of AI Using...
Optimised Edge AI for IoT
Double your AI performance in heterogeneous IoT data environments through continuous learning and fine-tuning, achieving a 2x improvement in system responsiveness and accuracy.
Private & Secure AI for IoT
Deploy Federated Learning Ops that safeguard data privacy and ownership, allowing you to implement AI solutions without compromising sensitive information.
Cost-Efficient AI for IoT
Reduce training costs by 100x and lower overall operational production costs by optimizing GPU/CPU expenses by 100 to 1000 times, making advanced AI accessible and sustainable even at scale.
Continuously Learning AI for IoT
Enhance the scalability of your AIoT systems by learning in parallel across more than 10,000 devices, without the need to centralise sensitive data.
Resilient AI for IoT
Our FL-Ops managed Edge AI provides robust lifecycle management with minimal dependence on cloud services and network stability, ensuring reliable on-device intelligence.
Accelerated AI for IoT
Rapidly deploy up to 500 devices in just 30 minutes and reduce the number of learning cycles by 90%, speeding up the time-to-value for your AI deployments.
OctaiPipe combines the power of Federated Learning and Edge AI to offer scalable, secure, and efficient AI solutions for IoT, which we term Federated Edge AI. This integration forms the foundation of secure, smart networks of devices across various industries.
OctaiPipe Removes Risk and Cost Barriers to AIoT at Scale
Rather than move data, we move models to the data - train models locally at nodes, then aggregate the models
Maximises privacy and security
Minimises data transfer and compute costs
Relies less on network or cloud connectivity
Immutable properties of dockerised pipelines ensure replicability and portability between devices and locations
OctaiPipe Is an Edge AI Platform for Critical Infrastructure IoT
Federated Learning for IoT
OctaiPipe delivers FL optimised for IoT, enhancing on device data privacy and security, and minimising network and cloud costs.
Edge FL-Ops
OctaiPipe maximises Edge AI performance and resilience, through automated FL-Ops delivering continuous collaborative learning across entire networks of devices.
FL for AIoT Toolkit
Pre-designed model architectures, graphical UI, tools and templates to speed up development of trustworthy AIoT solutions at scale
OctaiPipe Features
Rapid automated deployment with infrastructure as code
Cloud agnostic and portable
Seamless edge-cloud connectivity
Experimentation and model management tools
Automated and scalable model deployment to the cloud or the edge
AI managed FL-Ops for model deployment
Federated learning capabilities
Learning and prediction optimised for micro computers
OctaiPipe Runs on…
Compatible With All Major ML/DL Libraries
OctaiPipe builds models in ONNX format, making OctaiPipe solutions framework agnostic.
