Machine learning startups are gradually evolving at a faster pace and have emerged as one of the key players of IT firms
Machine learning is a blessing. The industrial sector saw a radical shift when machine learning and AI came into the limelight. Machine learning startups are gradually evolving at a faster pace and have emerged as one of the key players of IT firms. Machine learning refers to the development of intelligent algorithms and statistical modeling that aids in improving programming, without coding them explicitly. For example, ML can make a predictive analysis app more precise, with the passing time. ML frameworks and models require an amalgamation of data science, engineering, and development skills. This article lists the top 10 machine learning startups that would become big in 2022.
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.
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.
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.
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.
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 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 less data than required by traditional rule-based techniques.
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 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 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 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.