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10 AI Startups to Watch in 2022 10 AI Startups to Watch in 2022
The AI Startup Showcase at ODSC West is coming up fast, and we are so excited to showcase some of the... 10 AI Startups to Watch in 2022

The AI Startup Showcase at ODSC West is coming up fast, and we are so excited to showcase some of the leaders and innovators in the AI startups world. AI is changing the very fabric of our existence at home, at work, and everywhere in between, and it’s only fitting that we give you a small taste of what’s to come. Here are 10 AI startups you should be watching for the current (and next) big innovations in the field.

Tecton

Tecton offers a platform for real-time machine learning, helping companies build, manage, and operate their data pipelines. They raised USD 100 million in July from investors interested in the promise of MLOps. Company leaders count fraud detection, recommendation, and real-time pricing among their (long) list of potential use cases for the platform.

Aisera

Aisera is a service management platform specializing in AI, NLP, and NLU. It’s an “AI-driven service experience” designed to automate the complex ecosystem and monitoring of artificial intelligence solutions within the customer service world. They recently USD 90 million during an August funding round.

deepset

Natural language processing company deepset provides a framework to make it easier for developers to develop production-ready NLP systems more quickly without sacrificing quality. It provides an open-source framework for companies to deliver scalable, API-driven applications. The company raised $ 14 million during an August series A funding round.

Domino Data Lab 

MLOPs company, Domino Data Lab, wants to make it possible to unleash data science at scale. It offers an enterprise MLOps platform that makes it easier for data scientists to collaborate on model deployment and monitoring without vendor lock-in. In addition, developers can use their preferred languages and tools while ensuring governance and security. To date, they’ve raised over USD 220 million over the course of several funding rounds.

Snorkel AI

Snorkel AI helps speed the development of AI through Snorkel Flow, an AI development platform. It leverages programmatic data labeling and real-time training, regenerating entire training sets for production and iterations. They’ve been labeled by Gartner as a 2022 Cool Vendor and have raised USD 135.3 million over five funding rounds.

Ivy

Ivy is an open-source deep learning framework designed to unify ML frameworks and automate code conversions. The company wants to simplify and automate the complexity of building AI models and putting them into production by creating an abstraction over existing libraries and leveraging a single interface. It is a Y Combinator participant.

MosaicML

MosaicML makes machine learning more efficient through algorithmic “recipes” that users can compose together to improve training time and accuracy. It allows developers to find the most cost-efficient way to run training by visualizing the training process across combinations of clouds and hardware backends. Currently, the company is in private funding rounds but aims to cut the overall cost and overhead of deploying AI projects.

Superwise

Superwise offers a fully automated, enterprise-grade model observability. It integrates with any stack and is an API-first model. Superwise gives customers complete, self-service customization tools but also offers a set of templates for users who want guidance. Its assurance platform handles common AI flags, including bias detection and explainability.

Watchful

Watchful offers an interactive solution to data labeling, making it easier and faster for developers to train AI models. It uses programmatic data labeling and allows users to explore data holistically and validate it through a completely self-hosted solution. It integrates with any existing MLOps solution and installs within any secure environment.

Arrikto 

Arrikto offers a complete MLOps platform that aims to close technical gaps in machine learning workflows. It generates production-ready ML pipelines using a point-and-click method to help data scientists focus more on the data and less on the IT. In addition, it allows users to deploy on any platform and provides an end-to-end solution for production. 

See demonstrations of AI Startups at ODSC West

ODSC’s AI Startup Showcase coming up this November 3rd in San Francisco and virtually allows attendees to interact with the best and brightest in the field of AI. You can see these AI startups and more, network with leaders in the field, and continue on to receive training and support from the ODSC West conference.

Elizabeth Wallace, ODSC

Elizabeth is a Nashville-based freelance writer with a soft spot for startups. She spent 13 years teaching language in higher ed and now helps startups and other organizations explain - clearly - what it is they do. Connect with her on LinkedIn here: https://www.linkedin.com/in/elizabethawallace/

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