Top Machine Learning Startups that Aim to Excel in 2022
From very limited usage in the business world before 2012, machine learning dependency has gone up exponentially since the boom. Today there are 9k+ machine learning startups and companies according to Crunchbase. Here are the top machine learning start-ups that aim to excel in 2022.
Algorithmia — Algorithmia’s expertise is in machine learning operations (MLOps) and helping customers deliver ML models to production with enterprise-grade security and governance. Algorithmia automates ML deployment, provides tooling flexibility, enables collaboration between operations and development, and leverages existing SDLC and CI/CD practices. Over 110,000 engineers and data scientists have used Algorithmia’s platform to date, including the United Nations, government intelligence agencies, and Fortune 500 companies.
Avora — Avora is noteworthy for its augmented analytics platform, making in-depth data analysis intuitively as easy as performing web searches. The company’s unique technology hides complexity, empowering non-technical users to run and share their reports easily. By eliminating the limitations of existing analytics, reducing data preparation and discovery time by 50–80%, and accelerating time to insight, Avora uses ML to streamline business decision-making. Headquartered in London with offices in New York and Romania, Avora helps accelerate decision-making and productivity for customers across various industries and markets, including Retail, Financial Services, Advertising, Supply Chain, and Media and Entertainment.
Cognino AI — Cognino AI is a London-based startup specializing in research-led A.I. with deep expertise in self-learning Explainable A.I. They’re noteworthy for helping their clients accelerate data preparation to insight from large sets of unstructured data to support strategic decisions through real learning A.I.
Databand — A Tel Aviv-based startup that provides a software platform for agile machine learning development, Databand was founded in 2018 by Evgeny Shulman, Joshua Benamram, and Victor Shafran. Data engineering teams are responsible for managing a wide suite of powerful tools but lack the utilities they need to ensure their ops are running properly. Databand fills this gap with a solution that enables teams to gain a global view of their data flows, make sure pipelines complete successfully, and monitor resource consumption and costs. Databand fits natively in the modern data stack, plugging seamlessly into tools like Apache Airflow, Spark, Kubernetes, and various ML offerings from the major cloud providers.
Exceed.ai — What makes Exceed.ai noteworthy is how their AI-powered sales assistant platform automatically communicates the context of leads and enables sales and marketing teams to scale their lead engagement and qualification efforts accordingly. Exceed.ai follows up with every lead and qualifies them quickly through two-way, automated conversations with prospects using natural language over chat and email. Sales reps are freed from performing error-prone and repetitive tasks, allowing them to focus on revenue-generating activities such as phone calls and demos with potential customers.
Indico — Indico is a Boston-based startup specializing in solving the formidable challenge of how dependent businesses are on unstructured content yet lack the frameworks, systems, and tools to manage it effectively. Indico provides an enterprise-ready A.I. platform that organizes unstructured content while streamlining and automating back-office tasks. Indico is noteworthy given its track record of helping organizations automate manual, labor-intensive, document-based workflows. Its breakthrough in solving these challenges is an approach known as transfer learning, which allows users to train machine learning models with orders of magnitude fewer data than required by traditional rule-based techniques. Indico enables enterprises to deploy A.I. to unstructured content challenges more effectively while eliminating many common barriers to A.I. and ML adoption.
Netra — Netra is a Boston-based startup that began as part of MIT CSAIL research and has multiple issued and pending patents on its technology today. Netra is noteworthy for how advanced its video imagery scanning and text metadata interpretation are, ensuring safety and contextual awareness. Netra’s patented A.I. technology analyzes videos in real-time for contextual references to unsafe content, including deepfakes and potential cybersecurity threats.
Particle — Particle is an end-to-end IoT platform that combines software including A.I., hardware, and connectivity to provide a wide range of organizations, from startups to enterprises, with the framework they need to launch IoT systems and networks successfully. Particle customers include Jacuzzi, Continental Tires, Watsco, Shifted Energy, Anderson EV, Opti, and others. The particle is venture-backed and has offices in San Francisco, Shenzhen, Las Vegas, Minneapolis, and Boston. Particle’s developer community includes over 200,000 developers and engineers in more than 170 countries today.
Resurface Labs — Resurface provides a user-centric view into APIs that helps to democratize big data insights. Using AI-based techniques combined with their unique analysis techniques, resurface turns every API call into a durable transaction to speed troubleshooting, drive revenue recovery and improve CX. Resurface is gaining adoption in pre-production testing and Q.A., DevOps troubleshooting and root cause analysis, and real user data for data science spelunking across DevOps organizations today.
RideVision — RideVision was founded in 2018 by motorcycle enthusiasts Uri Lavi and Lior Cohen. The company is revolutionizing the motorcycle-safety industry by harnessing the strength of artificial intelligence and image-recognition technology, ultimately providing riders with a much broader awareness of their surroundings, preventing collisions, and enabling bikers to ride with full confidence that they are safe. RideVision’s latest round was US$7 million in November of last year, bringing their total funding to US$10 million in addition to a partnership with Continental AG.
