We decentralize the cloud to edge devices

NimbleEdge is a cross-platform ecosystem connecting all the user's devices to form a local cloud. These devices can collaborate with each other, offload computational tasks, and utilize idle resources on the private network bringing the best possible user experience. This ecosystem provides unmatched edge computing capabilities for personalization and real-time machine learning.

We have strived for a faster, secure and private world of connected systems.

Our team has built industry-leading solutions for privacy-preserving on-device learning and low latency cross-platform applications. NimbleEdge is the culmination of our insights and experience to overcome the limitations of centralized cloud-based services. We will change how your devices interact with each other and give control back to the edge.

Smart Local Cloud

We provide a novel local cloud that distributes computing across edge devices. These devices leverage each others' resources at ultra-low latencies.


Your data never leaves your trusted network of devices. All processing tasks are executed smartly on edge.


Each user's applications will be unique and personalized, reflecting their rare characteristics and preferences.


Our Services.


Personalised Recommendations

We are improving the current generation of recommendation engines by bringing personalized recommendation models. Instead of building one global model for all your users, you will have one model for every user. You will no longer need to focus on user features explicitly. The models will learn the user’s rare characteristics like his recurring payments and product bias that are often lost when trained over the entire population. We will be providing a complete on-device training and inference pipeline for building such personalized recommendation engines.

Real Time ML on the edge

ML on the edge is exploding day-by-day for video and image processing like Instagram reels and TikTok. Running these models on the cloud is costly, especially for videos, and needs on-device inference. Federated Learning (FL) based solutions can help personlise these models while ensuring data never leaves its location. It maintains user privacy and provides much lower latencies during inference. Our platform augments FL and ML inference with smart offloading to better utilize the on-premise assets. This provides a 10-100x speedup in task execution and improves the user experience of the app.



Our Technology.


Seamless Integration of Devices

We provide a multi-platform networking layer that unifies all your devices into a single entity. The inconsistencies between iOS, Android, Windows, or Linux won't limit you anymore. Gone are the days spent looking for a USB cable to share photos or play videos, just because AirDrop doesn't work with windows. The devices collaborate directly over Bluetooth, Wifi, or wifi-direct. All of this happens in a blink of an eye!

Edge Intelligence

We know you expect a lot from your devices, yet they always leave you high and dry. Our algorithms give these devices the intelligence necessary to collaborate and pool their resources so that you, as a user, can extract the maximum performance out of them. They are no longer mindless workers of the 2010s but intelligent agents of the 2020s. They can now distribute tasks amongst themselves and leverage the network's idle resources to improve your experience.



Our Team.

team people

Ayush Bansal

Co-Founder | CTO

Systems and Security Enthusiast. Ex-Tower Research. CSE @ IITK. Hacker. Developer. Geek.

team people

Varun Khare

Co-Founder | CEO

Machine Learning researcher and programmer, democratising AI via open-source, CSE @ IITK.


Contact Us.

Feel free to get in touch!

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