# Edge Impulse Reviews **Vendor:** Qualcomm **Category:** [MLOps Platforms](https://www.g2.com/categories/mlops-platforms) **Average Rating:** 4.5/5.0 **Total Reviews:** 11 ## About Edge Impulse Edge Impulse is an end-to-end platform for edge AI application development. We enable developers to use their own sensor, audio and vision data to train AI models for classification, regression and anomaly detection. Our platform is hardware-aware and developers can build models that scale from MCUs to NPUs. We support MLOps from start to finish - from initial data collection to monitoring the model in the field. ## Edge Impulse Pros & Cons **What users like:** - Users value the **extensive data augmentation and deployment options** of Edge Impulse, enhancing model performance across devices. (2 reviews) - Users find Edge Impulse's **ease of use** impressive, simplifying machine learning for various edge devices. (2 reviews) - Users value the **data augmentation and preprocessing tools** , which enhance training quality and improve model performance significantly. (1 reviews) - Users value the **flexibility** of Edge Impulse, allowing efficient model deployment across various edge devices. (1 reviews) - Users love the **easy-to-use graphical interface** of Edge Impulse, making machine learning accessible for edge devices. (1 reviews) - Scalability (1 reviews) - User Interface (1 reviews) **What users dislike:** - Users express a need for **offline documentation** options with Edge Impulse, especially in low internet access areas. (1 reviews) - Users feel the **lack of tools** for custom embedded devices limits their ability to fully experiment and optimize. (1 reviews) - Users find the **limited customization** options restrict their ability to create complex, specialized machine learning models. (1 reviews) - Users feel that support for **custom embedded devices** could be improved with additional features in the developer edition. (1 reviews) - Users find **model limitations** in Edge Impulse, wishing for more customization options and support for advanced architectures. (1 reviews) - Performance Issues (1 reviews) ## Edge Impulse Reviews ### 1. Using Edge as a fairly new user **Rating:** 5.0/5.0 stars **Reviewed by:** Georgian C. | Small-Business (50 or fewer emp.) **Reviewed Date:** August 21, 2023 **What do you like best about Edge Impulse?** The platform offers various deployment options, including exporting models to different formats that are optimized for specific edge devices. This flexibility ensures that your models can be efficiently utilized across your target hardware. **What do you dislike about Edge Impulse?** The platform might feel somewhat limited in terms of building very complex or specialized models. Users with advanced machine learning needs might desire more extensive customization options or support for more advanced model architectures. **What problems is Edge Impulse solving and how is that benefiting you?** Edge Impulse streamlines the complex process of developing machine learning models for edge devices. It provides an integrated platform that covers data collection, preprocessing, model training, deployment, and monitoring. This simplification saves developers significant time and effort compared to manually piecing together different tools and frameworks. ### 2. Empowering Edge AI Innovation: A Comprehensive Edge Impulse Review **Rating:** 5.0/5.0 stars **Reviewed by:** Alex G. | Small-Business (50 or fewer emp.) **Reviewed Date:** August 21, 2023 **What do you like best about Edge Impulse?** The platform provides a range of data augmentation and preprocessing tools that help enhance the quality of your training data. These features can be particularly beneficial when dealing with limited datasets, as they contribute to better model performance and generalization. **What do you dislike about Edge Impulse?** Although Edge Impulse provides a wealth of documentation and resources, some users might find it helpful to have offline documentation available for situations when they're working in environments with limited internet access. **What problems is Edge Impulse solving and how is that benefiting you?** Developing edge AI applications involves iteration and experimentation. Edge Impulse accelerates prototyping by offering a seamless workflow, allowing developers to quickly build, train, and test models on real-world data. ### 3. Using Edge daily **Rating:** 5.0/5.0 stars **Reviewed by:** Alexandru-Georgian C. | Project Coordinator, Small-Business (50 or fewer emp.) **Reviewed Date:** August 19, 2023 **What do you like best about Edge Impulse?** appreciate Edge Impulse for its user-friendly interface, machine learning capabilities tailored for edge devices, and its support for developing and deploying AI models for various applications **What do you dislike about Edge Impulse?** There are some limitations in terms of certain advanced customization options, compatibility with specific hardware, or the learning curve for those who are new to machine learning and IoT technologies. **What problems is Edge Impulse solving and how is that benefiting you?** Data Collection and Labeling: Edge Impulse simplifies the process of collecting and labeling sensor data, which is crucial for training accurate models. This benefits me by saving time and effort in manually managing and preparing my data. ### 4. A User Friendly and Powerful Machine Learning Solution **Rating:** 5.0/5.0 stars **Reviewed by:** Jon V. | Small-Business (50 or fewer emp.) **Reviewed Date:** August 31, 2023 **What do you like best about Edge Impulse?** I enjoys how easy it is to import and scale data. Overall Edge Impulse is a platform. It could be simplified for everyday users and offer more options for diverse applications of knowledge. **What do you dislike about Edge Impulse?** Whenever you retrain the model there are changes in the calculated accuracy results. This makes it difficult to rely on Edge Impulses classification accuracy consistently. **What problems is Edge Impulse solving and how is that benefiting you?** Their platform simplifies machine learning model training and deployment onto our devices significantly enhancing accuracy and performance in our systems. As a result our business benefits, from informed decision making. An improved overall user experience. ### 5. Edge Impulse for air quality alerting **Rating:** 4.0/5.0 stars **Reviewed by:** Gianfranco S. | Business Analyst, Small-Business (50 or fewer emp.) **Reviewed Date:** February 16, 2023 **What do you like best about Edge Impulse?** The look and feel and the ease of use. I like the simple and logical way the workflow is organised. **What do you dislike about Edge Impulse?** Minimal data import and data scaling abilities. One big problem I had was the time scaling, which is restricted to milliseconds - this is not helpful when importing data from many time series databases **What problems is Edge Impulse solving and how is that benefiting you?** AI has great potential for improving the accuracy of air quality sensor measurement data. One use case would be auto-calibration of low cost sensors who high accuracy sensors ### 6. Edge Impulse Review **Rating:** 4.0/5.0 stars **Reviewed by:** Sonali G. | Cloud AI intern, Small-Business (50 or fewer emp.) **Reviewed Date:** September 20, 2022 **What do you like best about Edge Impulse?** Edge impulse is one of the emerging platforms for embedded ML and is free for developers. Without specialised hardware like Arduino or raspberry pi, many real-time and time-consuming machine learning problems can be solved quickly. The best thing about this is you can use your mobile phone, computer or a supported development board. The data collection is super easy, and the dashboards help you manage your data. For example- you can view your previous data, projects and devices you used to connect etc. Very easy to use, just scan the QR code and the device gets connected via a link. Like any ML model, train and test data sets need to be created and you can create various labels for your reference. You can add filters to improve your results or for the desired conversion or input. It's straightforward; even if you are a beginner, just add the recommended filters, and they work great. Drag and drop approach solves most of the coding approach. There aren't many open source GUI-based approaches such as this one. **What do you dislike about Edge Impulse?** Not much really. It reduces the coding approach, which might be a habit for developers over time. But everyone is looking for GUI models these days, so might be helpful. On the other hand, it can be difficult for anyone looking for control of every single parameter and full customisation to the details of the approach. **What problems is Edge Impulse solving and how is that benefiting you?** For me, it was the accuracy issue. Every time you retrain your model, there are some internal changes to the previously calculated accuracy results by Edge Impulse, based on that, it creates another good classifier. ### 7. Edge Impulse Overview for it's users **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** October 03, 2022 **What do you like best about Edge Impulse?** It is a Machine learning based platform for businesses to enhance their experience on different embedded devices for audio-video visuals, sensors on a large scale. Through it's help, all the engineers or developers can solve the problems using Machine learning leading to the solution time to be very quick. **What do you dislike about Edge Impulse?** The platform in itself is good enough to use but it can be simplified and made easy to understood by common people also in terms of general analytics rather than just the developers or coders **What problems is Edge Impulse solving and how is that benefiting you?** Edge impulse is machine learning based platform, so giving the most optimum and accurate outputs in the minimum time is one of the major outcomes besides reducing the human efforts ### 8. Edge Impulse is a user friendly and an interactive software, which can be used and access easily. **Rating:** 4.5/5.0 stars **Reviewed by:** Sagar A. | Design Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** September 15, 2022 **What do you like best about Edge Impulse?** The user interface which lets a new user to interact and use the platform with confidence without hiding anything from user is one of the best things I like about the Edge Impulse **What do you dislike about Edge Impulse?** The interface on the mobile is needs to get improved compared to desktop view. Also the solution section could have more options to access variety and user can apply the knowledge with diversification. **What problems is Edge Impulse solving and how is that benefiting you?** The Edge Impulse is specifically used for Machine Learning which enables the deployment on various hardware to get amazing results and next to accurate predictions. And this benifts me to understand the ML deployment on various hardware. ### 9. Quick, almost instantaneous results. Refinement can be tricky **Rating:** 4.0/5.0 stars **Reviewed by:** Mario V. | Chief Technology Officer, Small-Business (50 or fewer emp.) **Reviewed Date:** September 16, 2022 **What do you like best about Edge Impulse?** Having a simple and consistent interface to build AI micro systems, with superb control over dataset collection, experiments, deployment (this is the secret sauce of this system, IMHO) **What do you dislike about Edge Impulse?** Not so detailed in giving information over NN structure, it would be nice to explore the overall implementation with some more details about "insiders" topics. ARM output in 32bits is someway hard to port to non-mainstream toolchains, like often happens in embedded devices. **What problems is Edge Impulse solving and how is that benefiting you?** Small NN compilation, model deployment, targeting real HW platforms like Raspberry PI and other minimal devices. Interestingly it supports also PC output which makes the solution more scalable. ### 10. GUI based tool for Edge machine learning **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Computer Software | Enterprise (> 1000 emp.) **Reviewed Date:** September 20, 2022 **What do you like best about Edge Impulse?** Edge impulse makes machine learning possible for Edge devices using an easy Graphical User Based interface. It supports a wide range of devices such as Rasberry Pie, Mobile phones etc. **What do you dislike about Edge Impulse?** Support for custom embedded devices could be enhanced. The company could provide a few more features in the developer Edition so that more and more people can try it. **What problems is Edge Impulse solving and how is that benefiting you?** Used this solution for a small project on Embedded devices. The development was quick as it provided a lot of GUI components for drag and drop. We had to write no code. ### 11. EDGE IMPULSE REVIEW **Rating:** 4.5/5.0 stars **Reviewed by:** Mukesh P. | Associate Business Manager, Enterprise (> 1000 emp.) **Reviewed Date:** September 15, 2022 **What do you like best about Edge Impulse?** Real time problems can be easily solved with the help of machine embedded system. **What do you dislike about Edge Impulse?** Machine learning is not everyone's cup of tea. **What problems is Edge Impulse solving and how is that benefiting you?** With the help of embedded sysytem MLOps are sloved within 5 minutes of traction time. - [View Edge Impulse pricing details and edition comparison](https://www.g2.com/products/edge-impulse/reviews?section=pricing&secure%5Bexpires_at%5D=2026-06-14+07%3A13%3A38+-0500&secure%5Bsession_id%5D=c0aa8be1-c4cb-42d0-b65e-2dda56310599&secure%5Btoken%5D=7915923ed9a40036f62e0bbe0ea523248453894f45056d9f8c1acd696bf3bbae&format=llm_user) ## Edge Impulse Features **Deployment** - Language Flexibility - Framework Flexibility - Versioning - Ease of Deployment - Scalability **System** - Data Ingestion & Wrangling **Deployment** - Language Flexibility - Framework Flexibility - Versioning - Ease of Deployment - Scalability **Development and Deployment - Edge AI Platforms** - Integration - Edge Optimization - Framework and Language Support **Model Development** - Language Support - Drag and Drop - Pre-Built Algorithms - Model Training **Management** - Cataloging - Monitoring - Governing - Model Registry **Model Development** - Feature Engineering **Operations** - Metrics - Infrastructure management - Collaboration **Management - Edge AI Platforms** - Device Scalability - Security and Compliance - Real-Time Monitoring **Machine/Deep Learning Services** - Computer Vision - Natural Language Processing - Natural Language Generation - Artificial Neural Networks **Machine/Deep Learning Services** - Natural Language Understanding - Deep Learning **Management** - Cataloging - Monitoring - Governing **Deployment** - Managed Service - Application - Scalability **Generative AI** - AI Text Generation - AI Text Summarization **Generative AI** - AI Text Generation - AI Text Summarization - AI Text-to-Image **Agentic AI - Data Science and Machine Learning Platforms** - Autonomous Task Execution - Multi-step Planning - Cross-system Integration - Adaptive Learning - Natural Language Interaction - Proactive Assistance - Decision Making ## Top Edge Impulse Alternatives - [Gemini Enterprise Agent Platform](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews) - 4.3/5.0 (651 reviews) - [Databricks](https://www.g2.com/products/databricks/reviews) - 4.6/5.0 (782 reviews) - [SAP HANA Cloud](https://www.g2.com/products/sap-hana-cloud-2025-10-01/reviews) - 4.3/5.0 (521 reviews)