Top Machine Learning Startups in 2024

Anicca Data Science Solutions is the one stop shop from objective to accomplishment in the data driven world. Our focus is to provide big data services and building algorithmic products to help business houses in process efficiency. The skill of Anicca is in putting together data platforms and applications with AI/ML solutions for addressing numerous modern day business challenges. The data space spans across multiple domains with numerous use cases. Anicca is on a mission to explore those strings of data and find insights that drives performances of the business practices. Anicca team strongly believe in transforming the way businesses operate with data driven decision making.

Chalk is building machine learning infrastructure to answer the world’s hardest questions. Our platform is built to power credit, risk, insurance, medical, and recommendation decisions for the world’s most innovative companies. Answering these complex questions requires sourcing data from a wide range of providers and rapidly iterating on feature definitions. Chalk makes it easy for machine learning teams to build high-performance pipelines that deliver data to models at the right time. We orchestrate infrastructure and automatically track data lineage so developers can work confidently and focus on their unique products and insights. Chalk is based in San Francisco, California. Meet Our Founders Elliot (linkedin.com/in/elliotmarx) started his career at Affirm where he built the early risk and credit data infrastructure system (the inspiration for Chalk). He then started Haven Money (with Andy) which Credit Karma acquired to power its banking products. Andy (linkedin.com/in/amoreland) met Elliot at Stanford admit weekend – Elliot was his room host and they’ve been best friends ever since. After school, Andy worked at Palantir on large government data infrastructure projects. He then founded Haven Money (with Elliot) which now powers Credit Karma Money. Marc (linkedin.com/in/marcff) spent many years at Google where he helped to launch the first version of Google Wallet. He went on to start Index which Stripe acquired as its in-store payment solution – it’s now called Stripe Terminal.

We’re a small (17 person) startup that got started out of MIT building tools for users to own their data. We’re freeing user data stuck in silos in tech monopolies using a combination of data regulation and decentralized tools, putting personal data back under control of the users who create it. We're well-funded by top VCs and are growing our team. For more information, visit vana.com

IV.AI is the world's smartest AI platform with a focus on enterprise. We have grown fast but aim to retain our scrappy nature that enabled us to build big ML models that outperform the industry standards. There are a lot of companies right now that talk about the potential impact of AI while we hustle hard and have actually proven the benefits repeatedly. See validation on the homepage (iv.ai) or via case studies (iv.ai/work) and press (iv.ai/press).

Jaxon dramatically increases AI project success rates, fosters collaboration, increases staff efficiency, and continuously learns what works and when. Through R&D efforts with the U.S. Department of Defense, Jaxon has created a way of simulating model system performance and getting the design right the first time. By formalizing the AI design process, design tradeoffs are able to be explored. It allows all talent levels to quickly and easily create, test, and iterate on AI system designs without the need for extensive coding or data preparation. It uses an AI-powered ‘Fact Checker’ to address the hallucination problem and bring trust into the output of large language models (LLMs). As a pre-trained Data Science Agent, Jaxon makes decisions based on established conventions and guides users to the right design. Rather than requiring the developer to specify every detail of how the application should work, this approach makes it much easier and faster to build applications.

Tiger Analytics offers data analytics and predictive modeling solutions for retail, social media, and online advertising sectors.

Footprint revolutionizes how businesses reduce carbon emissions, fast & efficient. The SaaS Plattform empowers businesses to get a tailored climate action plan and its implementation in record time. We leverage artificial and collective intelligence to accelerate global carbon reduction.

We’re building a platform that powers the biggest AI groups in the world, including OpenAI, Anthropic, Meta, and Google with human feedback data for evaluating and training their models. Surge was founded by former ML engineers focused on providing the highest quality data in the industry to push the state of the art forward. Instead of outsourcing to call centers overseas, we’ve built an elite workforce based in the US, custom annotation tools, and sophisticated quality control systems. Our product has been a “game-changer” for ML teams, and we’ve been able to run a profitable business from day one without raising venture funding.

We're a team of machine learning and product engineers training task-specific generative models for psychology. Our mission is to use AI to make mental healthcare more accessible and to help people change their lives in the ways they want. We partner with organizations around the globe and power use cases, including AI-assisted crisis text response and AI counseling, while securing best-in-class datasets to power our models. Success to us means every human being in need of support having somewhere to go. We're a well-funded, seed-stage startup backed by top-tier tech investors involved in ElevenLabs, Captions, Shopify, Plaid, Notion, Canva, Twitch, Airtable, and others. We're building a powerful team by empowering our engineers with the autonomy, flexibility, and resources to do their best work. We dream big and iterate fast. If that sounds like home, we'd love to hear from you. The Team Daniel started coding at age 8 and started training models in high school. At 16, he dropped out of high school and moved to London to pursue his study and research. He graduated university top of his class at 19 and was awarded ‘distinguished’ by Imperial for his post-grad research in AI for mental health. As an ML Engineer, he led Instabase’s pivot into GenAI. He raised $6M pre-team at age 22 to develop the tools for training task-specific generative models that now power our machine learning research. Neil dropped out of medical school to co-found Casper, the sleep company, which he helped grow to $500M+ in revenue and IPO’d in 2020. Improving wellbeing through sleep led him to mental health, where he joined the board of [PsychHub](psychhub.com). He’s invested in 200+ companies like Ro, Affirm, Relativity, Archer, Figure, and Together.AI. Our team has expertise in model training, product engineering, and psychology. Our engineers includes team leaders who have joined us as individual contributors, two former CTOs, and collective experience from across Big Tech.

EasySLR is an AI-first SaaS platform focused on systematic literature reviews. It provides features like AI-assisted study selection, intelligent data synthesis, transparent conflict resolution, comprehensive dashboard analytics, auto full-text retrieval, and customizable data extraction forms. These tools aim to make literature reviews faster, more accurate, and user-friendly, addressing the complex needs of systematic research innovatively and intuitively. The platform is designed by a team of experts with a strong background in building and scaling global products with a commitment to technological excellence and user-centric design. Our values are the driving force behind our mission. We champion innovation, nurturing a culture of continuous improvement that pushes the boundaries of what's possible in health research. Integrity and collaboration are the cornerstones of our foundation, ensuring that we operate with transparency and synergize diverse expertise to achieve common goals. We're dedicated to building tools that not only simplify the research process but also amplify its impact—because at EasySLR, we believe that the best way to predict the future of healthcare is to create it.