Engineering Trustworthy AI
Pixis IT is a research and development initiative dedicated to the rigor of machine learning. We architect the infrastructure, define the standards, and calculate the cost of privacy for the next generation of intelligent systems.
Our Research Focus
Compute Economics
Proprietary logic mapping model shapes to precise GPU/CPU envelopes to eliminate computational waste.
The Trust Tax Framework
Quantifying the financial and computational cost of adding Differential Privacy and security layers to models.
Algorithmic Auditing
Rigorous stress-testing methodologies for bias and drift to ensure model predictability prior to production.
Cloud-Native Infrastructure
Architectures for resilient systems across AWS, Azure, and GCP that enable automatic scaling.
Automated Governance
Turning 'policies' into 'code' by integrating automated compliance checks into CI/CD pipelines.
Regulated Environments
Specialized focus on Finance, Healthcare, and sectors requiring strict audit trails.
Portfolio
From award winning healthcare solutions to open industry standards, we create reliable AI that solves actual problems. Our work focuses on lowering costs, ensuring safety, and educating the community on how robust AI is truly engineered.
Would you like to view our Solutions?
We are dedicated to advancing the field of MLOps and Generative AI. Our research explores how to engineer compliant, scalable AI infrastructure. Interested in our methodologies or our platform, HealthNeem? Connect with us to learn more about our work.