About Edge Solutions Lab (ESL)
Edge Solutions Lab (ESL) is an end-to-end technology partner focused on bridging the gap between cloud and edge computing. We manage the entire lifecycle of edge innovation — from feasibility analysis and system architecture to custom hardware design, software engineering, AI deployment, and DevOps automation.
Our team has delivered mission-critical edge infrastructures across multiple sectors, including Healthcare & Remote Monitoring, Defense & Public Safety, Transportation & Logistics, Energy & Utilities (Mining, Oil, Gas), Agriculture, Retail, Telecom, and quick-service operations.
Among our partners are leading U.S. edge platform providers, defense technology innovators, energy enterprises, and advanced healthcare companies — all relying on ESL to transform their cloud-native systems into powerful, secure, and scalable edge environments.
Our Story
Edge Solutions Lab was founded in 2023 by the engineering team behind Hivecell — one of the pioneering distributed edge computing platforms in the United States. Building on years of experience in designing, deploying, and managing large-scale distributed systems, ESL emerged as a dedicated partner for companies looking to bridge the gap between cloud and edge.
Since its inception, ESL has delivered mission-critical edge systems for industries where reliability and real-time performance are non-negotiable — including Defense & Public Safety, Healthcare & Remote Monitoring, Energy & Utilities, Transportation, Retail, Telecom, and Industrial IoT.
Our engineers and architects have worked on breakthrough technologies for clients such as Point72, Stoneridge, Boehringer Ingelheim, and a range of U.S.-based defense startups. From wearable health monitoring devices sampling at 200Hz to air-gapped edge clusters capable of running large language models (LLMs) in extreme environments — ESL’s portfolio reflects innovation at the frontier of computing.
Leadership Team
Illia Kotlov
Ready to shape the future of Edge technology with us? Let’s build what’s next — together.
What is Cloud-to-Edge convergence?
Bringing the Cloud Experience to the Edge (Cloud-to-Edge Convergence) — means delivering the power, flexibility, and scalability of cloud technologies directly to local environments where data is generated. Instead of sending everything to distant data centers, edge systems process information on-site — enabling real-time decisions, lower latency, reduced bandwidth use, and improved data privacy. This is critical for industries like healthcare, defense, energy, logistics, and telecom, where speed, autonomy, and resilience are non-negotiable.
Edge Solutions Lab (ESL) builds full-cycle Cloud-to-Edge Convergence Solutions — combining software, hardware, and infrastructure — that replicate and optimize cloud capabilities at the edge. From AI model optimization and device integration to infrastructure setup, automation, testing, and scalable deployment, we help organizations operate smarter, faster, and closer to where it matters most.
Our expertise spans everything from real-time edge AI optimization and embedded system integration to ruggedization testing and environment simulation. We build automated testing rigs for device validation, engineer tailored deployment pipelines, and ensure quality across both hardware and software layers. Our DevOps and software engineers work in tight feedback loops to deliver scalable, secure solutions ready for production. From prototype to deployment — and long-term maintenance — we manage the entire lifecycle, ensuring performance, reliability, and adaptability in the most demanding environments.
Our team bridges the gap between software and hardware, enabling uninterrupted edge environments that operate reliably in the field. We don’t just replicate cloud services — we optimize them for edge performance, reducing latency and bandwidth demands through intelligent local processing and reliable system design.
Why now?
It is time to implement Cloud-to-Edge Convergence!
As digital systems shift closer to the source of data, Cloud-to-Edge Сonvergence has become a necessity, not a future trend. Advances in infrastructure and tools now make edge deployment practical, scalable, and cost-efficient.
Here’s why forward-thinking organizations are embracing the edge right now:
5G rollout
5G makes edge technology essential because it bridges the gap between ultra-fast connectivity and real-time data processing — unlocking new bandwidth-intensive use cases like autonomous vehicles, AR/VR, and smart manufacturing.
Edge-specific compute acceleration
Specialized chips (e.g., TPUs, NPUs, FPGAs) are optimized for tasks like video processing and machine learning inference directly on edge devices, enabling powerful local intelligence.
Mature edge platforms
Tools like K3s, AWS Greengrass, Azure IoT Edge, and Google Edge TPU make it easier than ever to build, deploy, and manage containerized workloads and AI models on distributed edge infrastructure.
Rise of edge-native applications
New applications — such as smart traffic control systems, drone fleets, industrial automation, and precision agriculture — are being designed from the ground up to operate at the edge.
Standardization and interoperability
Protocols like MQTT, OPC UA, and gRPC — along with open hardware/software standards — are streamlining integration and making multi-vendor ecosystems more manageable and future-proof.
On-device AI inference
Advances in AI model compression (e.g., quantization, pruning) make it possible to run intelligent models directly on mobile, embedded, or rugged edge devices without relying on the cloud.