Pittsburgh TechFest 2026

It only takes ½ of a “drop” of venom from an Inland Taipan snake to kill a five-ton elephant. It doesn't take a flood of venom to be lethal. It takes one bite, from one source, at the wrong moment.


External data works the same way. A single bad source flowing into an AI system can trigger the same kind of damage: hallucinations, bias, and decisions built on a foundation no one should trust. And unlike a snakebite, you often don't see it coming until the outcome is already wrong.


External data is nearly a trillion-dollar global market, yet the industry still has no reliable antivenom - no consistent standard for verifying where data comes from, whether it can be trusted, or whether it's fit for the system consuming it.


Andy Hannah, CEO of Blue Street Data, has spent his career building the infrastructure to change that. In this talk, he'll unpack the antidote most AI strategies are missing, and what it takes to keep the poison out before it ever reaches your models.
The payoff isn't just safer AI. It's the trust and harmony between people and machines that only comes when you know exactly what's flowing through the system.