Bring the AWS Cloud to Your Factory Floor
Sphere's AWS IoT Greengrass practice deploys AWS cloud capabilities – Lambda functions, ML model inference, stream processing, and device management – directly on your edge hardware. Process data locally, make real-time decisions, and sync with the cloud – all from the same AWS toolkit your teams already know.
Organizations around the world trust us
Why This Matters Now
Industrial organizations adopting AWS for IoT analytics face a fundamental tension: the insights they need most require real-time local decisions, but their existing AWS investments are cloud-centric. Running everything in the cloud adds latency, connectivity dependency, and bandwidth costs that make real-time industrial applications impractical.
1. Cloud Processing Can't Meet Industrial Latency Requirements
Sending plant floor data to AWS regions for processing and waiting for a response adds 50–500ms – too slow for production line control, safety systems, and real-time quality monitoring.
2. Cloud Connectivity Is Unreliable in Industrial Environments
Factories, mines, and remote facilities frequently experience network interruptions. Cloud-dependent systems fail during outages – often at the worst possible moment.
3. Bandwidth Costs Limit IoT Data Volume
Streaming all raw sensor data to the cloud is prohibitively expensive. Edge processing must reduce data volume before cloud transmission.
What Sphere Delivers
AWS IoT Greengrass extends AWS cloud capabilities – Lambda, SageMaker, Kinesis, and Secrets Manager – to run directly on industrial edge devices. Sphere's Greengrass V2 certified engineers design the edge processing architecture, develop the component library, and manage the deployment pipeline that gives your teams full cloud capability with local performance.
Greengrass V2 Component Architecture
Sphere designs and deploys custom Greengrass components for your specific industrial processes – local data filtering, aggregation, protocol translation, and ML inference.
SageMaker Edge ML Deployment
Deploy trained SageMaker models to edge devices via Greengrass – enabling computer vision, anomaly detection, and NLP inference to run locally without cloud round-trips.
Stream Manager & Local Storage
Greengrass Stream Manager manages local data buffering, priority queuing, and intelligent cloud sync – ensuring no data is lost during connectivity interruptions.
Secure Device Fleet Management
OTA component updates, remote configuration, and health monitoring across your entire Greengrass device fleet via AWS IoT Device Management.
Protocol Bridge & SCADA Integration
Translate OPC-UA, Modbus, MQTT, and proprietary industrial protocols to AWS standard format – connecting legacy equipment to the AWS ecosystem.
Edge Workflow Automation
Sphere uses Greengrass to turn industrial edge devices into active processing nodes, not passive data forwarders. Local workflows can validate signals, combine events, trigger actions.
Built On Industry-Leading Technology
Sphere's AWS IoT Greengrass offering is built for industrial environments that need cloud-grade services at the edge without sacrificing local performance or operational resilience. The stack combines Greengrass V2, Lambda-based edge processing, SageMaker model deployment, secure cloud synchronization, and industrial protocol support so manufacturers and infrastructure operators can run filtering, inference, storage, and control logic directly on site.
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Who This Is For
Local production monitoring, quality inspection ML, and MES integration with cloud aggregation for analytics.
Substation automation, grid edge intelligence, and demand response logic running locally on edge devices.
Warehouse edge processing for computer vision-based inventory counting and autonomous vehicle coordination.
Hospital device management, local patient data processing, and edge-based alert logic with HIPAA-compliant cloud sync.
Store-level edge processing for inventory management, queue detection, and loss prevention – with cloud rollup for chain-wide analytics.
Design Your AWS Edge Architecture With Sphere
Sphere's Greengrass V2 certified architects will review your current IoT architecture, identify edge processing opportunities, and propose an AWS Greengrass deployment design – in a free 45-minute technical session.
How It Works
Edge Architecture Design
Define edge compute requirements, select hardware (AWS-qualified devices), and design component architecture.
Greengrass Core Setup
Deploy Greengrass V2 nucleus on target edge hardware. Configure cloud connectivity and IAM roles.
Component Development
Develop custom Greengrass components for data processing, protocol translation, and ML inference.
Fleet Deployment
Use Greengrass deployment pipeline for controlled rollout across all edge devices.
Edge Architecture Design
Define edge compute requirements, select hardware (AWS-qualified devices), and design component architecture.
Greengrass Core Setup
Deploy Greengrass V2 nucleus on target edge hardware. Configure cloud connectivity and IAM roles.
Component Development
Develop custom Greengrass components for data processing, protocol translation, and ML inference.
Fleet Deployment
Use Greengrass deployment pipeline for controlled rollout across all edge devices.
ROI & Business Impact
Bandwidth & Latency Savings
Greengrass edge deployments reduce cloud bandwidth costs by 60–90% (by processing data locally before cloud sync), eliminate operational failures from connectivity interruptions, and reduce edge ML inference latency from 200–500ms (cloud) to under 50ms (local).
$200K–$800K Annual Savings
Average annual cost savings: $200K–$800K from bandwidth reduction and operational efficiency gains.
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Lee Ebreo
VP of Engineering at Credit Ninja
These things would not have been achievable if we did not build our own in-house system and if we did not partner with Sphere to help us achieve our goals.
Selah Ben-Haim
VP of Engineering at Prominence Advisors
Our experience with Sphere and their team has been and continues to be fantastic. We keep throwing new projects at them, and they keep knocking them out of the park (including the rescue of a project that was previously bungled by another vendor).
Ben Crawford
Senior Product Manager at Enova Financial
I would expect to be delighted. It's been a really positive experience, working with Sphere, and I would expect you to have the same.
Mark Friedgan
CEO at CreditNinja
Sphere consistently prioritizes the needs of their clients, demonstrating both agility and teamwork. As an offshore team, they have been an integral part of our organization and we plan to continue growing with them.
René Pfitzner
Co-Founder at Experify
Sphere provided excellent full-stack development manpower to augment our team and help push our product forward. They are easy to work with, tech-savvy and proactive.
Bruce Burdick
Chief Information Officer at Integra Credit
We've been working with Sphere and its excellent consultants since our founding. I've found that they are true partners in the success of our business.
Jemal Swoboda
CEO at Dabble
The resources and developers that Sphere Software provides are skilled and have the required technical expertise, but more importantly, they have helped us build a culture of excellence within our team.
Arthur Tretyak
Founder and CEO at IntegraCredit
With Sphere, we were able to migrate in half the time it would take to train an additional FTE… and for a fraction of the cost. Our experience with Sphere has been exceptional.
Lee Ebreo
VP of Engineering at Credit Ninja
These things would not have been achievable if we did not build our own in-house system and if we did not partner with Sphere to help us achieve our goals.
Selah Ben-Haim
VP of Engineering at Prominence Advisors
Our experience with Sphere and their team has been and continues to be fantastic. We keep throwing new projects at them, and they keep knocking them out of the park (including the rescue of a project that was previously bungled by another vendor).
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