Liquid Ai researches and develops artificial intelligence tools designed to enhance creative workflows. The company focuses on building next-generation AI applications specifically tailored for creative professionals. Their offerings aim to integrate advanced AI capabilities directly into existing creative processes.
Funding
$250M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Robotics developers and educators often lack a low‑friction, browser‑based environment to prototype, test, and benchmark autonomous algorithms against standardized tasks. Existing simulation tools require local installation, complex configuration, or costly licenses, which hampers rapid iteration and broader participation in robot challenges.
Solution
Liquid AI delivers a cloud‑hosted robot challenge platform that runs fully in the web browser, eliminating the need for local software setup. Users upload control code or configure visual programming blocks, which the service executes within a physics‑accurate simulation engine. Each challenge defines a clear success metric, and the platform automatically evaluates submissions, generates reproducible scores, and publishes results to a public leaderboard. The system exposes RESTful and WebSocket APIs, enabling integration with CI pipelines, educational LMSs, or external competition portals. All data exchanges are secured via HTTPS, and session state is maintained through standard browser cookies to ensure a seamless user experience. By centralizing compute resources, Liquid AI reduces hardware barriers and supports concurrent participants at scale.
Target Audience
The primary users are university robotics courses, research labs, and hobbyist communities that need an accessible platform for algorithm development and competitive benchmarking. Secondary customers include competition organizers and corporate training programs seeking a scalable, cloud‑based testbed for autonomous systems.
Features
- Browser‑native simulation powered by a deterministic physics engine (rigid body dynamics, sensor noise models) with no client‑side installation required
- Drag‑and‑drop visual programming interface plus support for Python, C++, and ROS‑compatible code uploads
- Automated challenge evaluation pipeline that computes task‑specific metrics (time‑to‑goal, energy consumption, collision count) and generates standardized scorecards
- Real‑time leaderboard with filtering by institution, skill level, and challenge version
- REST and WebSocket APIs for programmatic submission, result retrieval, and integration with external tooling
- Secure session handling via encrypted cookies and TLS‑protected data transmission
- Exportable logs and telemetry (trajectory data, sensor streams) in CSV and JSON formats for downstream analysis
- Multi‑tenant architecture that isolates competition environments while sharing underlying compute resources for cost efficiency