A New Approach to Delivering On-Device Intelligence
Train, Fine Tune, and Manage Federated AI for IoT
Interconnected devices are essential for the future resilience and performance of Critical Infrastructure. However, with increased connectivity comes increased risk and cost. Octaipipe enables trustworthy AIoT by embedded design, creating secure smart networks of devices that ensure the performance, resilience and efficiency of Critical Infrastructure.
Secure and Private FL for IoT
Make your IoT devices intelligent with private and secure AI. Leverage robust security and privacy features to ensure system security, data privacy, and compliance. Handle your sensitive IoT data confidently, knowing it stays securely where it belongs – at the edge.
Efficient and Resilient Edge FL-Ops
Decrease cloud dependency and reduce costs, all while accelerating the learning process. See significant cost savings in training, cloud infrastructure, and data transfer.
Trustworthy-by-Design AI for IoT
Build AIoT solutions you can trust to scale with OctaiPipe. Access a catalogue of optimised machine learning models to jump-start your journey. Make your AIoT systems more scalable and resilient with continuous collaborative learning.
Reduce error by
90%
with FL in heteregeneous IoT data
Avoid up to
£20 billion
in GDPR, HIPPA, & AI Act fines
Cut learning cycles by
90%
with data paralyzation
OctaiPipe Enables You to Finally Unlock the Value of AI Using...
Optimised Edge AI for IoT
Improved AI performance in heterogeneous IoT data with continuous learning and finetuning
Private & Secure AI for IoT
Federated learning for IoT without compromising data privacy and ownership
Cost-Efficient AI for IoT
On-device learning and prediction minimise network data transfer and cloud compute costs
Continuously Learning AI for IoT
Learn across thousands of devices without centralising data, making your AIoT systems more scalable
Resilient AI for IoT
FL-Ops Edge-managed AI gives you lifecycle management that is less reliant on cloud services and network stability for on-device intelligence
Accelerated AI for IoT
Deploy up to 500 devices in 3 hours and reduce the number of learning cycles by 90%
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.