I built METRIS™ because deploying AI today forces three questions that most organizations are deploying first and answering later: do the people deploying it understand what it is doing, can leadership see where it is running, and is there a human accountable for every automated decision.
These are not technical questions. They are questions about readiness. And underneath them sits one question the whole field is only beginning to ask out loud: when your board asks why your AI deserved confidence at the moment it made a decision that mattered, what evidence do you show?
I did not come to this from Stanford or Google. I came from years of lived work: as an educator, from an MS thesis on proteomics batch correction that taught me to find signal in noisy data, from research that taught me to respect empirical evidence, from cancer that taught me resilience, and from years of consulting on data science and AI for Fortune 25 to Fortune 100 companies that taught me to build systems that survive contact with the real world. All of it taught me to look at a problem from the inside out, which is exactly what AI deployment now demands, at every scale.
The gap keeps widening between what AI does and what we can prove it does. Someone has to close it. That is the work.
Suneeta Modekurty
Founder and CEO
