You can adopt AI in your company!

Complexity and costs of AI means your company can’t do it, right? Wrong. Our software can help you work on your most vexing, time consuming and high-ROI challenges. We help you do this:


xThink, learning deeply since 2003.

You can adopt AI in your company!

Complexity and costs of AI means your company can’t do it, right?

Wrong. Our software can help you work on your most vexing, time consuming and high-ROI challenges. We help you do this:

• Automate 80% of AI tasks; so your data scientists focus on the high-skill 20%. • Optimize the training of AI:

o Use Transfer Learning to reduce size of data sets required for training.
o Use Simulation to accelerate training.
o Use specialized, optimized hardware (GPUs, FPGAs, ASICs and Google’s Tensor Processing Unit, which combines CPUs and GPUs.)

• Open the “black box” of AI results, so you can make optimal business decisions.

• Modularize machine learning work, so you can distribute it across mobile devices and edge devices in your company and among your customers.

Let our automated software do these jobs:

Pre-process data: normalize, fill in missing values, identify data type (numerical, timestamp, etc.)

Prepare preliminary analysis: obvious categories and semantic hypotheses.

Identify features: Find the variables in your data that are relevant to your models.

Assess the library of AI algorithms: Automatically test the myriad of AI algorithms, and find the ones that generate the best results.

Our software can do a machine-learning proof of concept in days, not months.

Selected glossary

Black box: Today’s AI is heavy on neurons, and light on higher-level cognition. Our software is a “neuron whisperer.” We know what happens in the black box, and we can explain how the AI reached its conclusions.

Simulation: Synthetic data that is generated algorithmically to take on the characteristics of a massive variety of potentially real scenarios. AI can run through these algorithmic scenarios at lightning speed.

Transfer Learning: Where AI leverages knowledge from a related domain, such as language translation or image recognition, and applies it to your specific type of AI challenges.