Liquid AI

Liquid AI
Liquid neural networks for efficient AI, compact, energy-efficient models from MIT research.
About
Liquid AI, founded by MIT CSAIL researchers including Daniela Rus (CSAIL Director), Ramin Hasani, Mathias Lechner, Alexander Amini. Liquid neural networks achieve strong performance with millions vs billions of parameters. Emerged from stealth Dec 2023 with $46.6M seed. Teams look it up for Artificial Intelligence, Foundation Models, Efficient ML.
Liquid AI's efficient, device-native foundation models compete with larger models like Google's Gemini, particularly for edge AI applications and scenarios requiring lower latency and memory.
Liquid AI's focus on efficient, on-device AI models provides an alternative to cloud-based AI services like Microsoft Azure AI, especially for businesses with data sovereignty or offline environment requirements.
BMW, as an automotive manufacturer, could utilize Liquid AI's efficient and device-native foundation models for autonomous driving systems and in-car AI applications, where low latency and on-device processing are critical.
Samsung, a major consumer electronics company, could integrate Liquid AI's compact and energy-efficient models into smartphones, wearables, and home appliances to enable advanced AI features directly on devices.
Lockheed Martin, operating in aerospace and defense, could leverage Liquid AI's models for applications in connectivity-limited environments like satellites and for national security use cases requiring data sovereignty and on-device proces
JPMorgan Chase could use Liquid AI's technology for financial fraud detection and other latency-critical applications where sensitive data needs to be processed on-device to meet privacy and regulatory requirements.
Siemens Healthineers could implement Liquid AI's efficient models for medical imaging analysis and on-device AI in healthcare equipment, addressing privacy concerns and enabling faster insights without relying on cloud infrastructure.
Buyer fit inferred by StartupHub from what Liquid AI sells and public signals about each company. Only rows badged "already a customer" are confirmed relationships.
Strength of the site’s backlink profile, on Ahrefs’ 0-100 Domain Rating scale. Licensed third-party data, not our opinion.
How well an AI agent can read and use this site: structured data, clean markup, and whether key facts are reachable without running JavaScript. We scan the live site.
Google PageSpeed mobile performance for the company’s own site. Measured by Google, not by us.
