Best Artificial Intelligence Companies by 2019 Ratings

  1. Taranis

    Taranis is a leading precision agriculture intelligence platform that uses sophisticated computer vision, data science and deep learning algorithms to effectively monitor fields. Taranis offers a full-stack solution for high precision aerial surveillance imagery to prevent crop yield loss due to insects, crop disease, weeds, and nutrient deficiencies. Overseeing millions of acres of farmland in the United States, Argentina, Brazil, Russia, Ukraine and Australia, Taranis combines field imagery in three different levels from satellite images, through plane imagery to drone leaf level imagery, and uses AI deep learning technology to recognize crop health issues. Taranis targets high volume commodity crops which account for 70% of global crop market and gives farmers the tools to address issues in real time, increasing yields and cutting costs.
  2. Trifacta

    Founded in 2012 with deep roots in the computer science labs at Stanford and UC Berkeley, Trifacta is the industry pioneer and established leader of the global market for data preparation technology. Our products draw on decades of research in human-computer interaction, scalable data management and machine learning to make the process of refining data faster and more intuitive. Today, more than 50,000 Data Wranglers across 12,000 companies use our solutions. And every independent and analyst ranking has named Trifacta the number one data preparation solution worldwide.
  3. Nuro Inc

    We believe that great technology should benefit everyone. The team at Nuro is accelerating a future where robots make life easier and help us connect to the people and things we love. Together, we’re pushing the boundaries of robotics to improve human life. Dave Ferguson and Jiajun Zhu have devoted their careers to robotics and machine learning, most recently as Principal Engineers at Google’s self-driving car project (now Waymo). They founded Nuro in 2016 to harness the power of robotics and artificial intelligence to solve new challenges at a global scale.
  4. DeepScale

    DeepScale brings advanced, efficient perception capabilities to ADAS systems and AVs. We are geared to fundamentally change how we see cars, excuse us, how cars see us with a team of world-class ML/DL/AI engineers and their extraordinary expertise of efficient DNNs (deep neural nets). Currently partnered with OEMs, automotive suppliers, chip manufacturers and backed by major Silicon Valley VCs, DeepScale redefines safety for vehicles at all autonomy levels. We believe in improving our roadways today, not just focusing on an L4+ future. Our culture places emphasis on focus and passion, drives collaboration and cooperation, and encourages unique approaches to entrenched problems. DeepScale strives to always maintain a workspace environment of learning.
  5. Mapillary

    Mapillary brings together a global network of contributors who want to make the world accessible to everyone by visualizing the world and building better maps. Anyone can join and collect street-level images, using simple tools like smartphones or action cameras. With computer vision, we connect images across time and space to create immersive street-level views and extract map data. We believe that people and organizations working together in the open is the best way to collect, visualize and understand data about our world. Mapillary is not tied to any particular mapping platform and is based on the idea of people and organizations with various motives sharing data and helping each other. Our team’s mission is to build technology and tools to help understand the world’s places through images and make this data available.
  6. Perceptive Automata

    At Perceptive Automata, we’ve solved one of the hardest problems for robotic systems. We use our understanding of human behavior to enable the large-scale deployment of automated systems in human-dominated environments. The applications are countless as machines with modern AI are increasingly deployed in a broad range of fields as diverse as automated driving, factory automation, healthcare, and enterprise settings. We are starting with human behavior prediction and understanding for automated vehicles, and are working with OEMs, suppliers, and tech companies globally that are building or integrating automated driving systems.
  7. Mist Systems

    We built the first AI-driven Wireless LAN (WLAN), which makes Wi-Fi predictable, reliable, and measurable and enables scalable indoor location services like wayfinding, proximity messaging and asset visibility. In addition, Mist’s AI technology plays a key role in bringing automation and insight across the full IT stack, delivering seamless end-to-end user experiences and substantial IT cost savings.
  8. Sift

    We believe trust and safety are fundamental to every online interaction. As the pioneers of Digital Trust & Safety, we help more than 34,000 sites and apps navigate the fine balance between growing revenue and protecting their business. We believe legacy technologies are holding businesses back. We were the first to use machine learning for fraud prevention, and our customers see the results every day. The speed, accuracy, and scalability of our solution is unrivaled.

    Momenta, established in 2016, is one of the leading autonomous driving companies in the world. Momenta is building the “Brains” for autonomous vehicles. Our deep-learning based software in perception, HD semantic mapping, and data-driven path planning enables the realization of full autonomy. Momenta offers multi-level autonomous driving solutions as well as big data services. Momenta’s team is composed of some of the world’s foremost experts on computer vision and deep learning, including one of the authors of Faster R-CNN and ResNet, the most influential deep learning network, and winners of various top Computer Vision Competitions (ImageNet 2015, MS COCO Challenge 2015, ImageNet 2017, etc.).
  10. Benson Hill Biosystems Inc

    Here at Benson Hill, we believe the foundation lies in a healthy, sustainable food system rooted in diversity and choice. A variety of crops and product choices, optimized for different growing conditions by a community of innovators who are passionate about food and food production. So, how exactly do we do that? Nature, it turns out, is an incredibly generous and under-utilized source of genetic diversity that can improve food production and quality. We’ve built our company to enable innovators to collaborate and tap this diversity, wherever they may be in the food and agriculture supply chain.
  11. DeepMap

    Mapping: DeepMap delivers the best-in-class scalable and maintainable high-definition (HD) mapping service for autonomous driving. Our maps meet the safety, accuracy, and performance requirements for production-level autonomous vehicles. Localization: DeepMap offers centimeter-level real-time localization for various road types and driving conditions. We rigorously measure and benchmark the accuracy and performance for urban as well as highway driving. Our customers have full transparency into our localization performance in real time and at centimeter level. Simulation Data: Simulate with fresh, real-world data, not models. We provide 3D landmark features as well as a full 3D environment with true LiDAR intensity and RGB values data for simulation tools.
  12. AI.Reverie

    AI.Reverie is a simulation platform that trains AI to understand the world. Our simulation platform generates synthetic data to train and improve machine learning algorithms. The success of deep learning, a way to approach machine learning, has brought an insatiable hunger for data. However, data at scale is often proprietary, expensive, and laborious for people to manually prepare. The best way to deal with these challenges is with synthetic data — data created in virtual worlds rather than collected from the real world. Synthetic data is a powerful method for training AI because of its scalability and flexibility. Implementing solutions to narrow AI problems is expensive, but there is great potential in overcoming them using a synthetic data approach — data derived from a virtual photorealistic world that we’ve been pioneering at AI.Reverie.