Total Products under this Category: 60
Last updated: September 18, 2026
Why You Can Trust G2's Software Rankings:
G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category.
LF Edge is an umbrella organization that establishes an open, interoperable framework for edge computing independent of hardware, silicon, cloud, or operating system.
Particle is the leading edge-to-cloud infrastructure for the Internet of Things, helping thousands of companies power world-class connected machines, sensors, and devices. Particle provides everything you need to build an IoT product in one tightly-integrated platform, so you can focus your time and energy on what matters: your product, application, data, and customers. Hundreds of manufacturers, thousands of startups, and 260,000 developers use Particle to power their IoT products; to learn more, visit particle.io.
Average Rating: 4.5/5.0
Total Reviews: 180
"Good for prototyping and quick product deployments"
Rating: 4.0/5.0 stars
— Verified User in Utilities
"Particle is a best in class IoT platform"
Rating: 5.0/5.0 stars
— Jeremy L.
REBEL-Quad is a high-performance AI accelerator designed to meet the demands of hyperscale workloads. Utilizing advanced HBM3e chiplet-based architecture, it delivers exceptional energy efficiency and computational power, making it ideal for large-scale AI systems. By integrating four dies onto a single IC chip through state-of-the-art chiplet packaging, REBEL-Quad offers scalable solutions from single-card deployments to multi-rack configurations, effectively supporting multi-modal models and enhancing the sustainability of AI data centers. REBEL-Quad addresses the critical need for efficient and scalable AI acceleration in hyperscale environments. By delivering top-tier performance with reduced energy consumption, it enables organizations to deploy state-of-the-art AI services more cost-effectively. Its scalable design ensures adaptability to evolving AI workloads, providing businesses with a competitive edge in the rapidly advancing AI landscape.
Sensory SoundID was developed by Sensory, Inc., a company that has specialized in embedded voice, sound, and biometric intelligence for over two decades. Sensory’s technology powers billions of products across smart home, automotive, wearables, healthcare, and IoT, where low‑latency, privacy‑preserving edge AI is critical to user trust and real‑time responsiveness. SoundID extends this platform beyond speech, giving products the ability to understand and act on important environmental sounds. Sensory SoundID detects, classifies, and interprets real‑world sounds—such as alarms, sirens, glass breaking, baby cries, dog barks, coughing, snoring, and other events—directly on‑device without sending audio to the cloud. It uses a two‑stage detection architecture: a lightweight first‑stage model continuously listens for candidate events, and an optional neural revalidation stage confirms matches to reduce false alarms while keeping power consumption low. The SDK supports built‑in sound libraries, configurable “scenes,” and enrolled custom sounds, and it runs on a wide range of embedded processors used in automotive ECUs, smart speakers, wearables, robots, and industrial IoT devices. By processing sound locally, SoundID helps product teams add ambient awareness and safety features without recording or streaming continuous audio, supporting strong privacy and regulatory postures. Devices can detect critical events like smoke alarms, emergency vehicle sirens, glass breaks, or distress sounds and respond instantly, alerting users, adapting behavior, or coordinating with other systems, improving safety, accessibility, and user experience in homes, vehicles, workplaces, and public spaces. OEMs and solution providers get a modular, low‑power SDK they can combine with Sensory’s wake words, speech recognition, and biometrics to build differentiated products that “hear” and react to their environments while avoiding recurring cloud costs.
Stream Analyze provides an enterprise platform for Edge AI that enables companies to develop, deploy, run and manage analytical AI models across fleets of distributed devices – from microcontrollers to industrial gateways to unlock Decision Intelligence.
TAPPAS is Hailo's comprehensive software package designed to streamline the development and deployment of AI applications on edge devices. It offers a suite of fully functional application examples that integrate pipeline elements with pre-trained AI tasks, facilitating rapid prototyping and reducing time-to-market for developers.
Tokyo Artisan Intelligence (TAI) is a Japan-based startup established in 2020 that focuses on AI, deep learning, edge technology, FPGA, embedded computing, custom chip, and edge AI. The company's mission is to address societal issues such as labor shortage, technology succession, safety, and security in an aging society with a declining birthrate using advanced ICT technology.
uTensor is a free and open source embedded machine learning infrastructure designed for rapid-prototyping and deployment.
AI, cloud, and data technologies have evolved rapidly. In contrast, traditional control systems remain rigid and incompatible. Legacy systems often involve complex hardware and wiring and rely on old control technology. Modern manufacturers need a way to bridge legacy and emerging technologies to overcome the limitations of traditional systems and enable next-level productivity, quality, and sustainability. embedded ocean was established to fill this critical gap between modern digital technologies and traditional industrial technologies to unlock the potential of software-defined control. Xentara is a modern edge platform for industrial control - designed to meet the demands of real-time automation at the edge, empowering software-defined control systems. It offers both event-driven and cyclic processes - ensuring real-time responsiveness while maintaining scheduled efficiency designed for ultra-high precision (up to 100kHz) - tailored for the most demanding applications. Xentara functions as a bridge between OT (Operational Technology) and IT (Information Technology) - enabling seamless integration across domains, boosting interoperability & semantic abstraction - unlocking smarter, more connected, modular, and efficient industrial systems.
Vision AI Edge Models bring AI-powered visual inspection to the production line with all inference running on edge hardware. No video streaming, no cloud latency, no bandwidth costs: only the pass/fail verdict syncs to Zometric Core (on-prem or on-cloud), the video never leaves the device. That architecture means full line-speed detection with no throughput compromise, and image data that stays inside the plant. What it detects: * Visual defects: surface cracks, voids, scratches and dimensional errors. Proven on PCBs, stamped components, moulded parts and pharma packaging * Component verification: missing, wrong or misaligned components on assemblies. Solder joints, fasteners, label placement and fill levels caught before they move forward * Anomalies: an unsupervised model flags deviations from baseline with no labelled defect samples needed. Ideal for low-defect-rate and high-mix processes * Sorting and misclassification: wrong variants, mixed-part trays, incorrect orientation and mislabelled items flagged before dispatch or the next operation * OCR and code reading: part numbers, lot codes, date codes and barcodes read directly from the line, automating traceability capture without scanners or manual entry * Person identification: on-device worker registration for PPE compliance detection, fire-drill attendance and skill-matrix-based machine authorisation, so only certified operators run certified stations Deploy from a growing library of pre-trained models or train on your own images. Demonstrated applications include PCB missing-component detection, packaging print quality, flame-colour monitoring, liquid level and label verification. Results feed the Zometric platform's In-Process Quality, Inspection and Continuous Improvement modules with full defect traceability, so a vision-detected defect links automatically to the machine, lot and process data behind it. Serving automotive, electronics, pharma, chemicals and food and beverage manufacturers. Free pilot configurable in 2 to 3 weeks.
