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Empowering business operations with customized edge AI solutions

For most businesses, instant data processing gives a competitive advantage. Data intelligence keeps gaining more value than ever. Our edge AI computing solutions bring intelligence to data sources. Thus, it enables real-time decision making with minimal latency. As a result, it reduces the dependency on centralized cloud servers without compromising with security and efficiency.

  • Enhanced security as data stays local
  • Lower cloud and bandwidth expenses
  • Scalability and flexibility with adaptable deployments

Benefits of edge AI

Real-time decision making

Real-time decision making

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.

Reduced latency

Reduced latency

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.

Enhanced security

Enhanced security

By processing sensitive data at the edge, the system lowers the probability of data breaches and guarantees the security of vital information.

45% cost efficiency

Lower bandwidth costs

When data is processed locally, only substantial insights need to be sent to the cloud for analysis. This drastically lowers expenditure and bandwidth utilization.

Scalability

Scalability

Edge AI enables scalable solutions that can handle large volumes of data across distributed networks without overwhelming central systems.

Power efficiency

Power efficiency

Edge AI boosts power efficiency by processing data locally, reducing network data transmission, cloud reliance, and carbon footprint.

Tech Stack

  • Frameworks

  • tensorflow
  • pytorch
  • Onnx Runtime

  • Languages

  • c plus plus
  • python
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  • IDEs

  • Edge Impulse
  • vs-code
  • PyCharm

  • Deployment

  • Avnet /IOTCONNECT
  • AWS IoT Greengrass
  • Azure IoT Edge
  • Google Cloud IoT Core

  • Models

  • MobileNet (Edge-optimized)
  • YOLO (Tiny/Edge variants)
  • SSDLite
  • DistilBERT (Edge-optimized)
  • TinyML

  • Commercial Platforms

  • Nvidea Jetson
  • Qualcomm Snapdragon
  • Intel

Reduce latency and maximize efficiency – Adopt AI on the edge now!

Start your edge AI journey

Our AI on the edge services

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Edge AI consulting and strategy

Our strategic consulting services help businesses understand the potential of edge AI, evaluate their current infrastructure, and develop a plan for implementing edge AI solutions.

  • Edge AI readiness assessment
  • Custom edge AI strategy development
  • ROI analysis and business case development
  • Implementation planning and support

Vision AI at the edge

We create vision AI algorithms to process visuals like object detection, image recognition, and anomaly detection in real time – directly on edge devices.

  • Real-time visual inspection and quality control
  • Automated surveillance and security monitoring
  • AR/VR applications for retail and training
  • Edge-based facial recognition for access control

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Predictive maintenance at the edge

Use edge AI-based predictive maintenance systems to monitor machinery and equipment in real-time and anticipate issues before they happen to save maintenance costs and downtime.

  • Sensor data integration for real-time monitoring
  • Predictive analytics to forecast equipment failures
  • Automated maintenance scheduling
  • Real-time alerts for potential issues

Edge-based anomaly detection

Employ edge AI solutions to proactively address any problems by identifying anomalies in real time through a variety of data streams that involve network traffic, video feeds, and sensor data.

  • Real-time anomaly detection in industrial processes
  • Video-based anomaly detection for security and safety
  • Network traffic monitoring to detect cybersecurity threats
  • Customizable thresholds and alerts

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Integrating existing algorithms with edge AI

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Edge intelligence enables seamless integration of existing machine learning algorithms with edge computing frameworks. We assist businesses in optimizing and modifying their existing AI models so they can be effectively deployed and run on edge devices.

  • Optimize algorithms for lower power consumption
  • Ensure AI models can run on hardware with limited computational resources
  • Maintain AI model accuracy and performance
  • Enhance model agility and responsiveness

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Our AI on the edge solutions

Custom Edge Solution

Custom edge AI solutions

We leverage our expertise in AI, ML, IoT, and vision technologies to develop customized edge AI solutions for particular industry needs, ensuring scalable and effective functioning at the edge.

  • Tailored industry-specific solution design
  • Custom algorithm development and deployment
  • Integration with existing systems and processes
  • Comprehensive ongoing support and optimization

NLP Solutions

NLP solutions for AI on the edge

We offer cutting-edge natural language processing (NLP) solutions that are designed for edge devices, allowing for text processing, speech recognition, and real-time language analysis at the edge.

  • Optimized NLP algorithms for edge hardware
  • Multilingual support and sentiment analysis
  • Integration with voice assistants, chatbots, and other systems

Deploying SLMs

Deploying SLMs on the edge

Our team of developers is skilled in implementing small language models (SLMs) on edge devices, which eliminates the need for continuous cloud connectivity and guarantees effective and low-latency language processing.

  • Optimized SLM deployment for edge hardware
  • Fast, on-device language processing
  • Reduced cloud dependency and latency
  • Scalable and customizable for various applications

Industry-specific use cases of Edge AI

Our specialized edge AI solutions are made to fit the requirements of different industries:

  • Utilize real-time sensor and computer vision data to minimize downtime.
  • Enhance product quality through advanced quality control measures.
  • Implement predictive maintenance to prevent equipment failures.

  • Provide real-time patient monitoring for immediate care.
  • Enable diagnostics in remote areas to improve healthcare access.
  • Enhance the efficiency of healthcare delivery with instant data processing.

  • Use AI-powered analytics to boost customer satisfaction.
  • Manage pricing strategies effectively with real-time data.
  • Monitor and optimize inventory levels to reduce waste.

  • Continuously monitor crop health for timely interventions.
  • Automate irrigation systems to conserve water and resources.
  • Optimize resource usage to increase agricultural yields.

  • Improve fleet management with real-time data and analytics.
  • Enhance safety and efficiency in autonomous driving systems.
  • Monitor traffic in real-time to optimize routes and reduce congestion.

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Innovative AI solutions, delivering results at the edge

Take the next step towards edge AI innovation

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