Edge AI solutions
Make your systems think faster. Our solutions can help you create a real-time decision layer on your devices, spanning sensors, processors, and local machines.
Share your requirementMake your systems think faster. Our solutions can help you create a real-time decision layer on your devices, spanning sensors, processors, and local machines.
Share your requirementOur Clients
Many organizations in manufacturing, retail, logistics, and healthcare struggle with operational delays, network strain, and data privacy concerns as their AI workloads grow. With intelligent edge computing, we help companies deploy AI for real-time applications.
Our AI engineers understand unique industry and business requirements and accordingly build edge AI solutions that process data on all edge devices and environments. They support autonomous, real-time decision-making, so that companies like yours can reduce latency in their operations, ensure security and data privacy, and increase overall business agility.
We review your current devices and network, identify operational gaps, and outline real-time decisions that can move closer to the edge. And then, we define specific use cases and clear success criteria.
Our experts design the architecture, selecting the right mix of models, compute capacity, and device-level workflows so that they support stable and low-latency operations.
We build your imaging workflows and prepare data pipelines for your smart devices. And then, integrate visual and sensor inputs into the architecture so that each pipeline operates smoothly within the edge environment.
Our AI engineers develop and refine AI models to match your device capabilities and device types. Considering the operating conditions, we tune AI models for real-time output and make sure that your edge systems respond quickly and consistently.
Ultimately, we connect all components into a unified edge ecosystem. Our teams align models, pipelines, and device behaviors, and validate the results in real operating conditions.
After integration, we deploy models across edge devices and manage, versions, updates, and device health. Edge MLOps keeps deployments consistent in the field and ready for continuous monitoring and improvement.
Our support team provides monitoring and timely updates to keep your edge deployments accurate and secure. We also provide enhancements to meet your future requirements.
Applications like self-driving cars, industrial automation, healthcare, etc. require real-time analytics and decision making. Edge AI makes it easier by processing data locally.
Edge-based AI processes data at the edge. This minimizes the waiting time involved in moving data to and from the cloud, ensuring quicker reaction times.
By processing sensitive data at the edge, the system lowers the probability of data breaches and guarantees the security of vital information.
When data is processed locally, only substantial insights need to be sent to the cloud for analysis. This drastically lowers expenditure and bandwidth utilization.
Edge AI enables scalable solutions that can handle large volumes of data across distributed networks without overwhelming central systems.
Edge AI boosts power efficiency by processing data locally, reducing network data transmission, cloud reliance, and carbon footprint.
Our edge systems connect sensors, machines, and local hardware into one stable network. They create consistent data flow and support real-time decisions while maintaining secure operations across distributed environments.
Our AI models are built for your devices and tuned to work within their compute limits. They will give your operations faster responses, consistent output, and a smooth way to run intelligence directly on local processors and smart machines including industrial devices.
Our solutions deliver real-time inferences on edge devices with controlled versioning, monitoring, and lifecycle management. It keeps decisions steady and accurate across environments so that you can maintain predictable performance at the device level.
We provide analytics that run at the source and provide insights into operations as they take place. It can help your teams support automation and make faster decisions across plants, warehouses, retail floors, and field locations.
In all the solutions we build, security sits at the core of the architecture. It can help you with localized data handling, strong access control, and governance practices that align with your industry and regulatory expectations. Your teams can run operations across edge devices in regulated or high-risk environments.
Our AI engineers design solutions for edge-to-cloud orchestration. They blend edge processing with cloud-based intelligence to form one coordinated ecosystem. It helps you balance heavy workloads in the cloud with rapid device-level decisions while supporting your growth.
Our specialized edge AI solutions are made to fit the requirements of different industries:
Edge intelligence gives your current machine learning algorithms a direct path to run on local devices. Our teams adapt and tune your existing models so that they operate smoothly within edge environments. It creates a stronger decision layer on your devices and brings more stability to your operations.
Bring intelligence closer to your data and act on insights instantly
Start your edge AI journey
Industry
Legal
Technologies
Angular, Python, AWS, LangChain, Needle
Challenges
Business Impact
Explore how our AI solutions have driven transformation across diverse industries.
Softweb Solutions provided the AI-driven platform we needed — one that not only streamlined our claim processing but also significantly enhanced our operational efficiency. I highly recommend Softweb Solutions to any organization seeking to modernize and streamline their processes with intelligent automation. They have truly helped us elevate our claims management to the next level.
Stan Kanterman
President
Softweb has been our partner for over a decade in professional IT services including production and application development support. They support us on customer experience and cloud services as well.
Rimma Fuchs
IT Director
Edge AI is used to run artificial intelligence directly on local devices instead of the cloud. Processing data near sensors or machines enables faster decisions, lower latency, and better reliability in real-time environments.
Edge AI and cloud AI solve different needs, so the right choice depends on the use case. Edge AI supports real-time, low-latency decisions on devices. Cloud AI supports heavy computation, training, and large-scale analytics. Many systems use both together.
Edge AI is artificial intelligence that runs on local devices. Traditional AI usually runs in centralized cloud or data center environments. Edge AI processes data locally for speed and privacy, while traditional AI depends on network connectivity.
Edge AI devices are hardware that can run AI models locally. These include industrial cameras, sensors, gateways, embedded systems, smart machines, and IoT devices. Many operate in factories, vehicles, healthcare systems, and retail environments.
The latest advancements in edge AI technology include lightweight AI models, hardware acceleration, improved edge MLOps, and better edge-to-cloud orchestration. These advances enable faster inference, lower power usage, and smoother model updates across large device networks.
Edge AI is secure because data is processed locally on devices. Local processing reduces exposure during data transmission and limits cloud dependency. Security is strengthened through device authentication, encrypted storage, and controlled access at the edge.
Edge AI models are updated using centralized device and model management systems. New model versions are tested, securely pushed to devices, and monitored after deployment. Controlled updates help maintain consistent performance across edge environments.
Edge AI saves bandwidth by processing data locally instead of sending everything to the cloud. Only critical insights or summaries are transmitted. Local processing reduces network usage, lowers cloud spend, and improves operational efficiency.
Close the gaps in your edge environment
Tell us what is slowing you down, and we will build a real-time decision layer that brings consistent intelligence to every device you run.
