NimbleEdge Platform

Effortlessly deploy and maintain real-time machine learning models on mobile edge for session-aware, privacy-preserving personalization

NimbleEdge Platform

Benefits

Reduce cloud costs
associated with real-time data processing pipelines and inference

Privacy perservation
with minimal user data transmitted to cloud servers

Effortless scalability
with no need for reserve cloud capacity to handle traffic spikes

Minimal latency
with on-device inference removing need for high latency cloud API calls

NimbleEdge Platform

Benefits

Reduce cloud costs
associated with real-time data processing pipelines and inference

Privacy-preserving by design
with minimal user data transmitted to cloud servers

Effortless traffic scaling
with no need for reserve cloud capacity to handle traffic spikes

Minimal end-to-end latency
with on-device inference
eliminating need for latency-intensive cloud API calls

NimbleEdge Platform

Benefits

Reduces enterprise expenditure on cloud costs associated with cloud data stores, data processing pipelines, and backend services.

Improves model performance by leveraging real-time features and enabling per-user model personalization.

Scales infinitely & reduces operational complexity of managing cloud systems for throughput bursts, accelerating time to market

NimbleEdge Cloud Orchestration

NimbleEdge
Simulator

Run large scale ML inference and training simulations to estimate uplift benefits from real-time personalization

NimbleEdge
Cloud Service

Managed service orchestrating the machine learning pipelines for edge deployment

NimbleEdge
SDK

Ultra light-weight SDK integrated into client mobile app to enable on-device ML capabilities

NimbleEdge SDK

On-device Data
Warehouse

On-device managed database for storing persistent raw data such as real-time product-user interaction events

Data Processing Engine

On-device managed data processing engine for computing real-time user interaction based aggregate features

Ultra fast feature computation for each user by virtue of decentralized processing

On-device
Feature Store

On-device in memory processed data replica store for dynamically computed feature vectors from user events and cloud-based data

Precompute features within 80 microseconds, ~1000x faster than central cloud feature stores

NimbleEdge
Inference Engine

OS, CPU architecture and model specific compile and run time optimizations for minimum latency and resource consumption

End-to-end latency of <50 milliseconds from user interaction to prediction

On-Device Model Training

Unique model for each user for hyper-personalized results

5-10% uplift in model performance

Privacy-aware ML as PII is not transmitted to cloud servers for model training

NimbleEdge Cloud Service

Serialization and Orchestration Engine

Serializes and hosts ML models to be downloaded by mobile edge device

Orchestration engine to determine execution and data flow management

ML teams have complete central control of the on-device pipelines, including on-the-fly updates of data processing pipeline and model updates

Cloud Integrations

Pre-built integrations with AWS, Azure, and Databricks for leveraging existing models and cloud feature stores

Federated
Learning Platform

Aggregates on-device individualized models to train and update ML models

Ensures model training while Personally Identifiable Information (PII) remains on users’ mobile devices

NimbleEdge Platform Features

Features
Standard Suite
Premium Suite
On-device Data Warehouse
Data Processing Engine
Inference Engine
Managed Cloud Service Hosting
Access Control through CLI and Dashboard
Federated Learning Platorm
Hyper-Personalized On-device Training
Cloud Data Sync
Custom SDK Optimization
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

Get in touch
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

Get in touch
Nimble Edge Use Cases Graphical Representation
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FinTech
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

FAQs