NimbleEdge
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About
NimbleEdge is an on-device AI platform that enables personalized experiences at scale while preserving user privacy. It offers solutions for various industries like gaming, e-commerce, and media & entertainment, providing real-time GenAI driven co-pilots, search, and recommendations. The platform streamlines the AI lifecycle with on-device AI models, continuous deployment, session-aware event ingestion, and advanced monitoring. It leverages federated learning for hyper-personalization and reduces cloud costs and privacy compliance costs by utilizing the intelligent edge. The HOME Platform includes components like Edge Data Warehouse, Edge Inference Engine, and Edge Feature Store. NimbleEdge is SOC2 Type-2 and ISO 27001:2022 certified.
Platform
Features
• edge feature store & data orchestration plugins
• edge federated learning
• edge inference engine
• edge data warehouse and processor
• advanced monitoring and analytics
• session-aware event ingestion
• continuous deployment and modeling
• on-device ai models
FAQs
What is the product and what does engagement look like?
NimbleEdge HOME is a PaaS for deploying and managing your ML to the SDK, which has been integrated into your mobile app on the edge.
How is the NimbleEdge subscription priced?
NimbleEdge PaaS is a consumption-based pricing plan, based on the number of API requests made to the NimbleEdge SDK embedded in your mobile app. It is not based on data rate, user interaction or user activity or other data points required by the model to generate a result.
Describe the first 90 days of interacting with NimbleEdge as a team?
There will be three primary phases.Providing your team access to the NimbleEdge Cloud and SDK. The NimbleEdge engineering team partners with your ML and App teams to integrate your model of choice into the SDK.
Our data science team has an existing portfolio of models currently in-use. Are we limited to models that NimbleEdge produces or will the NimbleEdge HOME product support a combination of both?
Both. NimbleEdge has a data science team available to collaborate with your data science and app experts. However, once your first model is deployed to the edge, your data scientist and app experts will have the baseline knowledge to deploy additional models using the holistic NimbleEdge HOME platform
The risk and cost of storing PII in the cloud is well understood. How does NimbleEdge reduce both privacy risk and cost?
Very simply, we safeguard data which could be identified as PII, which the model requires in the device by not sending it to the central cloud. This allows you to take advantage of existing Android and IOS data protection and security your app has already factored.
Will my CISO and team be concerned that existing security policies will be impacted?
Since the SDK will be embedded into your app, the existing security measures implemented by the app team should not be impacted. If your compliance and risk teams identify a vulnerability in the NimbleEdge SDK, the NimbleEdge team will address the finding.
How will I leverage NimbleEdge Federated Learning into our modeling process?
Now that you have a single model deployed across all apps in-use by your customer’s model performance, not data, is collected across the deployed customer base. NimbleEdge Federated learning will take this performance data, modify the model and deploy when you are ready.
Pricing Plans
Premium
Unknown Price• SDK for inference
• NimbleEdge Cloud service
• SDK training
• Additional NimbleEdge consulting services
Job Opportunities
There are currently no job postings for this AI tool.
Ratings & Reviews
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