For Apps with 1M+ Daily Active Users

On-device ML platform for real-time personalization in
mobile apps

Delight users and boost conversion with session-aware, real-time machine learning, without breaking the bank on cloud infrastructure costs

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
Use Cases

Unlock the power of on-device, real-time personalization in your mobile apps

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E-Commerce
Read your users' mind with real-time personalized recommendations, search results and promotions

Boost conversion and average order value by delivering tailored user experiences, which adapt in real-time based on in-session user behavior

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Nimble Edge Use Cases Graphical Representation
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Gaming
Elevate user experience with real-time personalized purchase recommendations, promotions and game balancing

Improve gamer engagement and cut dropoff with game experiences personalized in real-time to incorporate in-session user behavior

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Nimble Edge Use Cases Graphical Representation
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FinTech
Gaming
Enhance user experience with robust fraud detection and real-time personalized cross-selling recommendations

Improve ML model performance and slash cloud costs by using on-device ML to capture real-time user interactions in fraud and personalization systems

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Nimble Edge Use Cases Graphical Representation

NimbleEdge on-device ML platform provides both orchestration and execution capabilities for real-time 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