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Private AI Edge (edge of Cloud, on-premise) solutions will be commonplace as expectations grow for real-time insights, reactions and experiences of AI.
Private AI with Edge and AWS is a cutting-edge solution for deploying AI models at the edge, ensuring your data remains secure and compliant.
This innovative approach unlocks the potential of Private AI in safeguarding sensitive information or providing inference for data in locations that have no connectivity.
Leveraging Storm Reply’s AWS, IOT and AI capabilities, this solution brings the best of AWS to the Edge.
Use Cases:
Sensitive or Confidential Data: Ideal for companies handling sensitive data that cannot leave the premises, such as financial institutions, healthcare, defence and manufacturing.
On-Premises Data: Perfect for environments where data must remain on-site, like manufacturing plants, banks and hospitals.
Limited Connectivity: Essential for locations with no connectivity, ensuring continuous AI operations without relying on external networks, such as cruise ships, remote teams and secure or underground buildings.
Our Private AI solution is designed to manage sensitive data that must remain onsite or data situated in areas without connectivity.
Private
Edge and AWS
AI
Isolation and Control: By hosting Gen AI locally, it is isolated within the organisation’s network, limiting access to only those who have explicit permissions. This reduces the risk of unauthorized interaction with sensitive data.
Data Ownership and Control: The business maintains full control over their data usage, ensuring that only authorized parties can interact with it through the Gen AI model, thus safeguarding against unauthorized data breaches or misuse.
Compliance with Data Protection Laws: Local hosting allows the company to manage data according to relevant laws, such as GDPR, by controlling where and how your data is used and stored.
Proximity-based Processing: This feature involves processing data closer to its source, which reduces latency and bandwidth usage. It is particularly beneficial for real-time applications where immediate responses are crucial.
AWS managed: Edge computing managed by AWS enables you to secure, update and manage multiple devices on your premises, or even mobile locations. OTA (over the air updates) from AWS Cloud to the Edge means you can update apps, databases, and LLM (large language models) that deliver Private AI capability.
Enhanced Data Sovereignty: By processing data locally, edge computing protects personal information from exposure over the internet. This approach also aids in complying with local data regulations, as each location can manage its own privacy concerns effectively.
Automation of Business Processes: AI can automate repetitive or time-consuming tasks across industries, such as customer service (e.g., chatbots), supply chain management, financial trading, and healthcare (e.g., diagnostics).
Enhanced Decision-Making: AI-powered tools help organizations make data-driven decisions in areas like finance, healthcare, marketing, and risk assessment by analyzing large datasets and providing insights.
Personalization of User Experiences: AI is used to create personalized interactions for users, such as recommendation systems, virtual assistants and personalized healthcare treatments.
Integrate with control systems, devices & data.
Choose your Edge compute & integrate with AWS.
Train AI models in AWS.
Deploy trained models to edge devices for real-time inference.
If you would like to explore how to reduce latency, improve security and increase privacy by deploying AI models at the edge of your network and you wish to discuss these topics further, please contact us for a free demo or a 1-hour advisory session.