Hyper-Personalization
on Mobile App for your customers, in real time
Increase revenue by delivering hyper-personalized content and experiences in real-time with Edge Intelligence while reducing cloud costs and improving user engagement modelling by efficiently scaling real-time ML with federated learning.
Tailor your app experience in real-time for your users, optimizing the conversion funnel through unparalleled hyper-personalization.
Skyrocket your app's performance with minimal latencies (<20ms) and manage bursts of throughput while keeping costs in check.
Pinpoint the perfect audience at precisely the right moment using hyper-personalized offers and messages that resonate.
Safeguard your organization against the threat of privacy compliance penalties while maintaining data integrity and security.
what is hyper-personalization?
Hyper-Personalization is the future of crafting amazing user experiences by leveraging the Intelligent Edge. Brands unleash hyper-personalization by understanding user engagement data deeply and adapting to individualized preferences in real-time. Intelligent Edge brings 100 million unique ML models for 100 million users.
Unlock The Edge For Your Industry
Maximize fintech momentum with widespread, personalized modeling. Continuously elevate user experiences through comprehensive, real-time insights into 360-degree engagement and transaction history.
Enhance mobile journey through user-aware sessions and pertinent recommendations, optimizing the customer experience. Optimise the conversion rate and average order value by increasing engagement and exploration
Personalize game-play predictions at scale and reduce fraud at super fast latencies. Manage huge user activity bursts while simplifying the operational complexities.
Deliver Hyper-Personalization without worrying about Scalability
Factoring in the impact to market cap in addition to near term savings, scaling companies can justify nearly any level of work that will help keep cloud costs low.
data protection
Hyper-personalization does not need to come at the risk of collecting and exposing sensitive consumer data. Keeping real-time ML processes at the edge safeguards PII.
speed drive
Leveraging the edge enables high volumes of real-time hyper-personalized recommendations without incurring latency problems.
Our Intelligent Edge Platform provides both orchestration and execution capabilities for hyper-personalization.
Leverage real-time ML to deliver hyper-personalization for performance uplift — without the cloud cost burden and privacy risk.
Maximize Your Gains With NimbleEdge
Infinite Scalability,
Made Simple
With edge new customers does not increase cloud costs because compute cycles and training execution happens locally. This simplifies scaling your infrastructure by 2-3X with predictability in cost and infinitely scalable deployments.
Unparalleled
Hyper-Personalization
Federated Learning (FL) gives each customer their own unique individualized Machine Learning (ML) model which makes real time, more accurate and more relevant recommendations.
While Reducing...
Privacy
Compliance Costs
Smart phones have the computing horsepower to execute and train Machine Learning (ML) models on the devices themselves, providing relevant recommendations without sharing the PII with cloud. Save up-to 80% of your compliance cost with privacy-preserving algorithms.
Spiraling
Cloud Costs
Utilizing the edge means less frequent updating of the central model, fewer compute cloud cycles, less data storage and less data transfer.
Achieving real-time ML at scale is made possible by harnessing the power of the Intelligent Edge.
Create the Intelligent Edge with the NimbleEdge Platform
Edge Data Warehouse and Processor
On-device managed database and query engine providing real-time persistent information at latencies of <1 millisecond.
Edge Inference Engine
Fully compatible with existing ML models written in PyTorch, Tensorflow, LightGBM, XGBoost, ONNX, and Numpy. No more rewriting models for the edge.
Edge Federated Learning
Privacy-preserving on-device training suite, enabling enterprises to train 100 Million+ individualized Machine Learning (ML) models across 100 Million+ user devices.
Edge Feature Store & Data Orchestration Plugins
A continuously cloud-synced, in-memory processed data replica that precomputes features <80 microseconds – 1000x faster than central cloud feature store, for real-time inferencing.