What you get
Real-time distributed intelligent decisioning is disrupting virtually every sector.
Use cases that are powered by real-time AI
Manufacturing
Forecast to unlock $740BN of value in manufacturing by 2030
Key use cases include:
- Advanced predictive maintenance
- Precision monitoring & control
- Augmented reality & remote expert.
Supply chain, logistics & transportation
Forecast to unlock $280bn of value by 2030
Key use cases include:
- Real-time routing & optimisation
- Final 100 yards delivery
- Predictive fleet maintenance.
Retail & Consumer Packaged Goods
By 2027, 66% retailers will deploy edge computing in store
Key use cases include:
- Hyper-personalisation through customer devices
- Point of Sale (PoS) and Kiosk real-time intelligence
- Smart stock management.
Where we're delivering value
- Automotive: Manufacturing quality and predictive maintenance, Data security for EV charging stations
- Supply chain: End-to-end sourcing for procurement
- Retail and consumer: Smart meter management, real-time claim monitoring and quoting.
Our clients
- Global Enterprises: enhancing business efficiency and performance
- Private Equity Investors: creating value for their portfolio companies
- Systems Integrators: bringing innovation to service offerings.
Our example use cases
OT-IT convergence for end-to-end predictive maintenance
Benefits
- End-to-end ability to monitor, manage and optimise manufacturing efficiency
- Optimised scheduling of scarce maintenance resources, reduced down-time and higher quality production
- Unlocking new strategic decisioning at the centre through access to machine and site level operational insights e.g. diverting operations away from sites with predicted issues.
Challenge
Modern manufacturers rely on complex, expensive machinery to produce precision parts at high volume and quality. Unexpected down-time or reliability issues impact production schedules, profits, and customer satisfaction.
Fast and accurate detection and prediction is critical to rapidly and proactively respond to issues and minimise impact.
Solution
Our approach is end to end and event driven, to address monitoring and prediction at machine and site level (Operational Technology - OT), and strategic decisioning at the centre (Information Technology - IT), with innovative technologies including:
- BondzAI: Adaptive AI that monitors machine vibrations to detect anomalies and predict failure events in real-time; it learns directly from operators in the field versus time-consuming cloud re-training and deployments.
- Volt Active DB: A real-time decisioning and database technology enabling fast ingestion and correlation of multiple events across an edge site (e.g. factory). Through its Java engine, AI and logic are deployed right next to the data enabling milliseconds response.
- Akamai Connected Cloud: Site-level events are forwarded and distributed to enable fast access regionally and centrally.
Challenge
Supply chains are highly distributed with heterogenous data and they operate in silos. This makes them difficult to monitor, impeding the ability to act on events in a timely manner. This leads to issues with a large radius of impact on suppliers, partners and customers.
Solution
Our approach is a supply chain digital twin representing your assets and their environment as a digital model. Crucially, the digital model is distributed, rather than centralised, to reflect the real-world situation.
The key is to act through the digital twin in real-time with localised intelligence while enabling aggregation of insights for broader intelligence at regional and central level for end-to-end decisioning. To do this we leverage technologies including:
- Olympe.io: To rapidly ingest heterogenous data across distributed sources and orchestrate decisioning workflows
- Volt Active DB: To run quantized AI and TinyML on data in distributed locations
- NATS.io: Event bus provides high-performance and efficient sharing of events through a distributed event driven architecture underpinning the supply chain environment.
Digital twins for supply chain efficiency and resilience
Benefits
- Enables real-time observability with automated intelligent decisioning and action
- Enables continuous optimisation that increases efficiency and resilience of a complex distributed network of assets and partners.
Harnessing the power of AI at the Edge: transforming predictive maintenance and automation
Bondzai joins Linebreak to deploy real-time AI for predictive maintenance and quality in manufacturing
