CIOInsider India Magazine
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Yashwant Dagar
Founder & CEO
Over the past decade, Edge Computing has witnessed significant advancements, evolving into a crucial component of modern technological landscapes. As industries increasingly adopt IoT devices, edge computing enables data processing closer to the source, reducing latency and optimizing real-time decision-making. This shift is empowering various sectors, from robotics, automotive and healthcare to retail and manufacturing, with more efficient and intelligent systems.
However, end customers developing edge solutions often face several challenges. Selecting the right device can be difficult, as silicon vendors often present benchmarking results that can confuse customers, making decision-making complex. Vendor lock-in is another significant hurdle, as embedding software and deploying machine learning models on the edge requires extensive time and expertise. Each new silicon device necessitates a lengthy evaluation process, which delays the product development cycle. Furthermore, customers must choose between off-the-shelf hardware and custom built solutions, each carrying its own costs and risks.
To address these challenges, Intelligent Edge Systems is revolutionizing the field with innovative solutions. Their Intelligent Pipeline Generator (IPG) & Intelligent Edge MLOPs (IEM) are already being shipped to key strategic customers with enhanced edge AI workflows, while their third flagship product, Intelligent IOT SDK (IIS), is set to ship soon. In the past year, the firm has successfully supported six diverse clients, including those in robotics, pharma, and retail, offering comprehensive, end-to-end Edge AI solutions. Their vision is to overcome the obstacles faced by edge computing professionals, paving the way for more seamless and efficient technology deployment.
CIO Insider engaged in a one-on-one interaction with Yashwant Dagar who is the Founder & CEO of Intelligent Edge Systems. Let’s read on.
What are your flagship Edge AI solutions, and how do you help organi -zations fully harness the capabilities of embedded systems?
At Intelligent Edge Systems, we offer two flagship products, namely Intelligent Pipeline Generator (IPG) and Intelligent Edge MLOps (IEM), both of which are already available to our customers. IPG automates the creation of hardware-optimized software for popular edge AI platforms like Blaize's Graph Streaming Processor, NXP Imx8 & NVIDIA Jetson Orin. This eliminates the need for a dedicated embedded software team, as it automates code writing, software architecture generation, integration, and debugging.
IEM streamlines the entire machine learning workflow, covering model creation, data labeling, training, optimization, and compiling for edge devices with pushbutton functionality
A key part of our success in optimizing edge AI solutions is our collaboration with Blaize. Their GSP is purpose-built for low-latency, energy-efficient performance which is essential for real-time edge environments. The flexibility of Blaize’s architecture integrates seamlessly with our IPG tool, making it easier to build and deploy optimized solutions quickly across appli-cations without extensive rework.
IEM streamlines the entire machine learning workflow, covering model creation, data labeling, training, optimization, and compiling for edge devices. One of its standout features is the push-button functionality, allowing users to monitor and retrain models directly from the field to ensure performance and accuracy.
Looking ahead, we’re working on the Intelligent IoT SDK (IIS), designed for IoT customers, and tools for Intelligent System Design, PCB, and CAD automation.
Our workflows reduce development cycles by up to 5x and lower costs, giving our customers more room to experiment and innovate faster. Powered by our indigenous technology and several pending patents, our tools continuously improve as Generative AI evolves. Our silicon-agnostic approach and customer first mindset set us apart in delivering adaptable solutions across industries.
Could you provide a case study that demonstrates the challenges faced, the solutions you implemented, and the positive results achieved?
We recently delivered a Smart Retail Vision AI solution for an Indian retail brand. The primary challenge which we
faced was creating a cost-effective solution that could integrate with the existing infrastructure of low-cost cameras while supporting five AI use cases. The solution also had to be affordable from the perspective of Indian customers. Given the budget constraints, we evaluated various hardware options and narrowed it down to low-cost processors with builtin AI capabilities. Using our IEM workflow, we quickly trained multiple advanced machine learning models, leve-raging auto labeling and performance evaluation within just three weeks.
Additionally, IPG allowed for rapid code generation and deployment across multiple devices simultaneously, speeding up the prototyping process. Thanks to this efficient development cycle, we were able to go from device requirements to a working prototype in under two months, much faster than the initial six-month timeline, which had higher risks and costs. The solution met both the budget and performance targets.
How would you characterize the team behind the development and deployment of these solutions? What level of expertise do they contribute?
We are a blend of industry veterans, experienced professionals, and bright young minds. About 80 percent of our core R&D team comes from top-tier engineering colleges in India. This includes IITs, NITs, DTU, and PEC, with many holding PhDs and Master's degrees in relevant fields. We also have industry veterans with over five decades of combined experience in R&D, product development, and business. On the R&D front, our team includes seasoned inventors with over a dozen global patents and numerous research papers. From a business perspective, we have leaders and advisors experienced in scaling Embedded and IoT products to over $300 million in revenue, with a deep understanding of the U.S. and European markets.
What is the future roadmap for Intel ligent Edge Systems?
The last year has been a pivotal one for us, where we focused on building our core technology, fostering relationships with key customers and partners, and validating our product and market strategy. In the coming years, we aim to scale our R&D, expand our product portfolio, grow our customer base, and continue leading in GenAI-powered software workflows for Edge AI and IoT. We also plan to venture into manufacturing, incorporating GenAI workflows for hardware, PCB, and CAD design, while forming strategic partnerships to position ourselves as a global leader in Edge AI and IoT products and solutions.
