TL;DR
Existing robots learn generic averages from massive datasets. Our robots learn from customer feedback.
We solve the RL feedback loop for robotics, allowing our robots to learn from your specific standards via an automated reward pipeline that combines customer feedback with an intelligent judge model. This is the only way to capture the multi-trillion dollar “long tail” of unique, high-aggregate-value business tasks.
We’re live with real customers today and aggressively improving model performance. Our team led autonomy at Parallel Systems (series B startup; 100M raised) and scaled AI revenue for Facebook’s recommendation systems.
The Problem
The real market for general purpose robotics is a multi-trillion dollar “long tail” of differentiated tasks. This is the market that traditional automation can’t touch. The core technology to solve this is finally viable, but the long tail means the only path to success is adaptation to millions of specific customers' needs.
We’ve spoken to countless customers. No one has ever asked for a human form factor. They demand three things: reliability, throughput, and control. They want boxes packed in a specific order or towels folded lengthwise twice. Traditional learning algorithms don’t give this customer specificity.
When you work backwards from these actual customer requirements it becomes clear that we’re missing the bridge between customer feedback and model improvement.
Our Approach
We build robots that learn from customer feedback and improve continuously.
- Adaptive Intelligence: At its core, an automated pipeline that combines customer feedback with a judge model to RL fine-tune a model and steer it towards positive behaviors, as defined by customers.
- Pragmatic Hardware: A mobile robot with a wheeled base and bimanual arms. Designed for long uptime and high throughput.
Our models can learn new behaviors on-site with less than an hour of data, delivering low cost, effective automation immediately.
If you’d like to learn more, please reach out to us: hello@parametric.company.
