The case for verifiable AI
Fact AI Lab builds AI automation for the workflows businesses can't afford to get wrong. We specialize in SaaS, real estate, and financial services — where the ROI from automation is high and the tolerance for errors is low.
The technology to verify AI outputs before they reach your team exists. The tooling to make that verification production-grade — with eval metrics, privacy controls, and audit trails your legal team can sign off on — did not, until now.
Pedram Agand, Founder
I am an AI systems researcher with a focus on reliability, verification, and production deployment of language models. My academic background is at Simon Fraser University, with published research at IROS and NeurIPS workshops on robotic perception and grounding problems that share structure with LLM hallucination.
Before founding Fact AI Lab, I watched compliance teams at financial services firms reject genuinely useful LLM applications — not because the technology was bad, but because they could not explain outputs to examiners. The problem was not the model. The problem was the absence of verifiable infrastructure around the model.
Fact AI Lab is the infrastructure I could not find when I needed it.