Who we are?
We’re pioneers in trustworthy and responsible AI technologies. Our team consists of AI researchers, ML engineers & software developers to serve you in all aspects.
What we do?
We help you keep the risks of your AI in control, set up your AI risk & quality management frameworks and bring together all the stakeholders in an all in one comprehensive platform. We certify your AI systems, even in an automated manner.
VALIDAITOR offers a rich set of tests to collect performance and robustness metrics. You can define tests and automate them to run on your models. It is your CI/CD tool in machine learning.
VALIDAITOR enables you to monitor the performance of your production models in real-time. Define metrics to watch for and Validaitor handles the monitoring for you. It’s your SoC tool in machine learning.
VALIDAITOR lets you stay in compliance with the upcoming AI regulations. Run automated tests on your models and get the compliance checks and reports from these tests.
Quality Assurance for ML
We partner up with you to ensure that your ML systems are secure, fair, robust and compliant.
We’re on a mission to keep AI secure and trustworthy.
AI is revolutionary. AI is transformative. AI is used in many high-risk application areas that concern human safety and security. We enjoy the capabilities of the modern AI systems. BUT…
AI systems are vulnerable to adversarial attacks. They can be hacked easily. They can leak private information and they can be biased as well. Being aware of the problems is the first step in fixing them. We took that step and moved further to establish trust in AI.
We specialize in bringing trust to the AI applications and systems. We establish a broader vision to AI quality by bringing security, safety, privacy and robustness analysis into the reach of the ML practitioners.
We combine cutting-edge AI research with practical industry experience.
Our research and engineering teams strike a sweat balance between the research and industry. We take state-of-the-art methods and techniques from research and distill them for the practitioners by taking applicability and practicality into account.
We know your pain, we were there.
We’re not setting up academic playgrounds. We’re coming from right in the middle of the industry and we suffered from the same pains and problems. That’s why we’re cracking the barriers of ML testing and quality assurance.