dox
Company Details
- Location
- Beirut, Lebanon
- Website
- http://dox.tech
- Founded
- 2017
- Employees
- 4-10
- Fundraising
- Not Fundraising
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Learn more about
dox
The problem we're solving
Batteries are really hard to predict and manage. Battery manufacturers try to compensate by adopting rigorous testing measures and by providing warranties to their customers. However, we’re still seeing today that these processes are inefficient (example: Chevrolet Bolt Recall costs GM $1B)
Our solution
dox's vision is to provide an end-to-end battery intelligence system that will reduce battery uncertainty and costs. Currently, we have 2 products:
- Battery predictive analytics: helps battery fleet owners reduce battery waste, sudden failures, and unnecessary costs
- Battery testing optimization: helps battery manufacturers accelerate their testing processes while ensuring the safe operation of batteries in real-world environments.
Our differentiator
Features/tools provided, covering the entire battery value chain, algorithms used for prediction, open-source (after product launch).
Biggest achievement
We were able to achieve a 95% prediction accuracy on the MIT/Stanford dataset (battery life cycle assessment tests) which is superior to the accuracy they were able to achieve (90%).
The problem we're solving
Batteries are really hard to predict and manage. Battery manufacturers try to compensate by adopting rigorous testing measures and by providing warranties to their customers. However, we’re still seeing today that these processes are inefficient (example: Chevrolet Bolt Recall costs GM $1B)
Our solution
dox's vision is to provide an end-to-end battery intelligence system that will reduce battery uncertainty and costs. Currently, we have 2 products: - Battery predictive analytics: helps battery fleet owners reduce battery waste, sudden failures, and unnecessary costs - Battery testing optimization: helps battery manufacturers accelerate their testing processes while ensuring the safe operation of batteries in real-world environments.
Our differentiator
Features/tools provided, covering the entire battery value chain, algorithms used for prediction, open-source (after product launch).
Biggest achievement
We were able to achieve a 95% prediction accuracy on the MIT/Stanford dataset (battery life cycle assessment tests) which is superior to the accuracy they were able to achieve (90%).