For Apps with 1M+ Daily Active Users

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.

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Use Cases

Unlock The Edge For Your Industry

USeD in
FinTech
E-Commerce
Gaming
Overcoming fraud, omnichannel complexity and financial data compliance challenges.

Maximize fintech momentum with widespread, personalized modeling. Continuously elevate user experiences through comprehensive, real-time insights into 360-degree engagement and transaction history.

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Nimble Edge Use Cases Graphical Representation
USeD in
E-Commerce
Solve the challenges of item discovery, cross-selling, and cart abandons.

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

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Nimble Edge Use Cases Graphical Representation
USeD in
FinTech
E-Commerce
Gaming
Win with intuitive and customized gameplays that smoothly scale on activity bursts.

Personalize game-play predictions at scale and reduce fraud at super fast latencies. Manage huge user activity bursts while simplifying the operational complexities.

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Nimble Edge Use Cases Graphical Representation

Deliver Hyper-Personalization without worrying about Scalability

Contain Cloud Infrastructure Costs

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.

Tradeoff: Scale vs. Infrastructure costs
Highest level of
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.

Tradeoff: Personalization vs. Privacy
Accurate predictions &
speed drive

Leveraging the edge enables high volumes of real-time hyper-personalized recommendations without incurring latency problems.

Tradeoff: Latency vs. throughput

Our Intelligent Edge Platform provides both orchestration and execution capabilities for hyper-personalization.

Edge pipelines with on-the-fly updates
Edge pipelines with on-the-fly updates
Cloud-to-Edge Orchestration
Fully-Managed Platform-as-a-Service
red sun

Leverage real-time ML to deliver hyper-personalization for performance uplift — without the cloud cost burden and privacy risk.

The X-Factor Your Business Needs

ROI & SCALE

The ROI & Scale are always on the rise, all while there is a continued reduction in Operational Complexities, Privacy Risk, Fraud, API Calls etc.As a result, the gap only widens with NimbleEdge’s X Factor.

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Nimble Edge Home Platform

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.

Leverage the Intelligent Edge with the HOME Platform

Edge Data Warehouse and Processor

On-device managed database and query engine providing real-time persistent information at latencies of <1 millisecond.

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Edge Inference Engine

Fully compatible with existing ML models (PyTorch, Tensorflow, LightGBM, XGBoost, ONNX, and Numpy) – no more rewriting models for the edge.

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Edge Federated Learning

Privacy-preserving on-device training suite, enabling enterprises to train 100 Million+ individualized ML models across 100 Million+ user devices.

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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.

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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.

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FAQs