Our story
Building the operating system for physical work
Praxis guides frontline teams through physical work, verifies that it was done correctly, and learns from every execution.
We're founded by people who have built the systems behind physical work from both sides — computer vision and multi-sensor fusion on one, and the supply chain and retail operations that run on them on the other.
Our mission is to give every physical operation a memory: a trustworthy record of how the work was actually done, and a way to use it, so the same mistake stops repeating across shifts, lanes and people.
What drives us
Our core values guide everything we do as we build the technology that lets physical operations learn from their own work.
Customer Obsessed
We deeply understand and empathize with our customers so much so that we are there whenever they need us and for whatever they need us for. We only build products and features they love and are exceptional.
Gritty
The people and the company adapt to change even when it's hard. We work through problems and don't give up when it's challenging. We never say we can't do it.
Selflessness
Each individual seeks what is best for the company. We do not have egos when it comes to how and who sources ideas. We are empathetic of others views. We help each other out.
Honesty & Candor
We demonstrate radical candor and honesty. We are transparent about short term vs long term decisions and are willing to receive and provide feedback.
Grow Fast
We always seek to grow. We are open to doing things that are uncomfortable. We experiment, and if we fail we do it quickly and bigly. We encourage divergent thinking.
Meet Our Team
Nader Ahmed
Nader Ahmed
Robotics engineer with deep expertise in computer vision and physical-world autonomy. Led U.S. Department of Energy–funded initiatives solving hard perception and navigation problems in unstructured environments. Now building the warehouse-mapping foundation for the next generation of AI-driven distribution.
Anuj Natraj
Anuj Natraj
AI practitioner with expertise in natural language processing and computer vision. Previously worked in defense technology, applying machine learning to mission-critical systems. Now focused on building robust AI solutions that address complex, real-world problems at scale.
