An average human takes 100 seconds to understand a financial transaction. The Ntropy API understands it in 100 milliseconds.
A framework that makes it easy to create pipelines and run them on existing pipeline platforms.
Successes, benchmarking, and how to maximize your performance. Bringing meta-learning to production.
We present how we use cross-encoder transformers and attention masking for superior performance
How we were able to achieve the best accuracy for multilingual named entity recognition.
Categorizing Data from Financial Transactions matters. Here’s how you do it and why it’s important.
We could not stay silent about what is going on in Ukraine. Here is what we are doing to support
Maintaining backwards compatibility is one side of the coin. The other issue is to make sure the new
A scalable O(N*K) solution for sequences of size N and max intervals of size K.
Practical use cases of sentence clustering.
How we leveraged open-source and cloud providers to lower training costs and decrease training time.
We have heard multiple arguments that ML should be built in-house.
Our favorite use cases for a transaction categorization API
What is transaction categorisation and why is it important?
What does transaction categorization mean and what products and services can it unlock?
The Ntropy API enables companies to understand financial transactions with super-human accuracy.
Can machine-learning models be deployed to production from day one, with nearly no internal data?