Systems | Development | Analytics | API | Testing

In this episode of The Innovation Blueprint, Roman Havrylyuk (CEO of ORIL) talks with Joe Stockton, Co-Founder & CEO of Oyster Data, about how Oyster Data is transforming real estate operations with advanced asset management and AI-driven solutions. Learn how predictive maintenance is reshaping property performance and what the future holds for PropTech in 2026 and beyond. What we cover in this episode.

I’ve been testing OpenClaw, a fully autonomous agent that lets you remote control your entire system via Signal. It’s incredibly powerful to text your computer from a coffee shop and have it execute tasks, but you’re essentially handing the keys to your digital kingdom to an LLM. The Golden Rule: Trust, but verify. I’m using Proxymock to sniff every single API call going in and out of the agent. If there’s a data leak or a "hallucination" that tries to wipe my drive, I see it first.

Imagine managing multiple clients and instantly answering "Who has the lowest cost per conversion?" without opening a single spreadsheet. We're going to show you how to use Databox MCP to query multiple client accounts simultaneously and run an instant performance benchmark to compare ad spend and conversion rates side-by-side. About this series: This video is part of our "Chat with Your Data" series, where we explore the Databox MCP.

Why do large language models hallucinate? It's not a modeling problem. It's a data and context problem. This video breaks down why AI fails in enterprise environments and what it takes to get reliable, verifiable answers from your AI systems. When AI doesn't have governed access to live data, no understanding of your business rules, and no guardrails to keep it grounded, hallucinations aren't just likely. They're inevitable.

As AI agents act on enterprise data, governance failures become business liabilities. Learn why fixing them downstream won’t work anymore.