Mindgard vs Rhoda AI

Rhoda AI focuses on embodied AI: its Direct Video Action (DVA) model learns generalist robot policies from over 1 million web videos, then adapts to specific tasks with only 1–10 hours of trajectory data. The FutureVision video-predictive control allows the robot to generalize to unseen tasks, and long-context memory enables in-context learning. The custom robot platform is built for heavy-duty work – 25kg rated payload (40kg peak) with safety-rated brakes in every actuator and 3 years continuous operation at rated payload. In contrast, Mindgard is a software security platform that maps AI attack surfaces (including shadow AI), runs automated red teaming to find exploitable vulnerabilities, and provides psychometric agent profiling to fingerprint AI behaviors. It includes a GuardBuster tool for evaluating guardrails and integrates with Burp Suite and CI/CD pipelines. Mindgard's recent disclosures (Cursor 0day, ChatGPT generating violent imagery, Claude posing as a medical professional) demonstrate its focus on production AI agents and LLMs, not physical robots.

Both Rhoda AI and Mindgard use contact-based pricing, meaning no public pricing tiers are available. For Rhoda AI, this is typical for custom industrial robotics – each deployment likely involves hardware purchase, integration, and possibly a service agreement. The $450 million Series A at a $1.7B valuation suggests significant per-robot cost and enterprise contracts. Mindgard's contact pricing is also common for enterprise security platforms. While no numbers are shared, the product is likely subscription-based (annual or monthly) with pricing scaling by number of tests, agents, or integrations. Comparison is impossible without quotes, but the investment in Rhoda AI implies a higher upfront cost, while Mindgard may offer a lower entry point for teams already in a security toolchain.