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  • founders@recognant.com

Frequently Asked Questions (FAQ)


Are you a neural network?
No. We believe our system to be superior in most use cases, but the traits and scores from our system can be used as features to train Neural Networks. This can reduce the cost of training a neural network by more than a million times.

Are you machine learning?
Yes, but not how most people mean it. Machine Learning is automated pattern recognition. It is bucketing. Recognant uses epistemology, and so a thing can be partly in a bucket, and partly out of it. This allows for a much more human way of viewing the world.


Are you AI?

Yes. Recognant is an AI unlike any other out there.


How are you different?

How much time do you have? Recognant is Transparent ML, and eXplainable AI. That means our system is not a black box. Our system has a high Emotional Intelligence, and that allows for more human-like interactions. Rather than an ontology, or hierarchy we use an epistemology which allows for things to be lots of things, or composites of things, or differences from things. Our system uses heuristics rather than a probabilistic model. The list goes on. Basically everything everyone else is doing, we gave up on 10+ years ago. We are what’s next.


How fast are you?

Speed is a weird thing in computers. We are massively parallel for most the tasks we approach. In that sense we have near infinite speed. For any one tasks we are highly efficient. We are so many orders of magnitude faster than NTLK, or CoreNLP that we have given up on benchmarking against them, plus we can run on a cellphone, and neither of those would fit in memory, let alone the speed on that slow a CPU.  Typically we are 3,000-50,000 times cheaper to run than anything that competes with us in the on premise space. In the SaaS space we are significantly cheaper per call, but because we are faster per call, we create additional savings because the software waiting for the response doesn’t have to wait as long.

Get the API

Our API is self service and easy to get started with. Natural Language Processing on demand, at scale, and under budget.