Short answer: Jim Olsen says ModelOp's discovery service queries enterprise platforms like Amazon Bedrock and Microsoft Copilot for models not yet in the inventory, then starts a configurable life cycle to bring them into compliance.
Watch this answer from Episode 55 (starts at 6:05) · Episode 55 notes and transcript
From Episode 55: Every Client Is Fortune 500. What Do They Know About AI That You Don’t?, starting at 6:05.
Sam Nadler [6:05]: Okay. And my follow-up question is, like, we've we've covered, token usage, and I think that makes a lot of sense on how they're evaluating, implementing or delivering, AI solutions to their customer base or even internally. There's these other features, security, compliance. How does ModelOp help in those areas?
Jim Olsen [6:24]: Yeah. Well, let me give you a quick demonstration of how we drive that process that will kinda tie all that together. So for instance, what we're gonna do is we have these concepts of basically life cycles that are configurable, that can enforce different policies, but they drive the process through rather than being something that passively sits back. So we're gonna walk through a really, really simple example today where we actually use our discovery mechanism to query our enterprise platforms, find new models that aren't registered in the system yet, so called shadow AI. And then we're going to start a process to say, hey, we discovered one. These are what you got to do to make sure, it's up to compliance standards in this case on that. So what we're going to start with is actually our discovery service where we're going to go out, we can query different platforms that are out there that are used. We're not interested particularly in desktop level because the reality is everything will have AI in the long run. Basically, Windows has AI built in. You use a particular API, it may have AI backing it.
Jim Olsen [7:31]: You don't know and etcetera. But what we really are interested in from our standpoint is the ability to actually discover, yeah, we've got these enterprise services such as Agent three sixty five, Amazon Quick, Amazon Bedrock, etcetera. What is actually being run out there? Microsoft Copilots, there's people developing these within the enterprises all the time on their own, and we don't always know about it. We don't, know what's being done, and that's a liability to the business because those enterprise level resources actually can have access to proprietary information. So we wanna make sure that they're so called brought into the fold, automatically brought into the inventory, as I said. It's called the shadow AI problem. Some people look at it from a desktop perspective. We're looking at it from an enterprise resource level perspective of these real platforms that people are utilizing and utilizing a multiplicity of them. So it can be very hard to track down all of these different usages that are occurring out there.
Jim Olsen [8:31]: So what our system's doing right now is actually scanning for those and reconciling it against known items within the inventory on that. And then what's gonna happen is when we bring them in, when we bring a new one in, we're gonna start this process where we go through and reach out to people to go get documentation, use our agents to auto complete forms based on the documentation they have, our own AI and agents, and then actually look at applicable policies based upon those answers on that kind of things on there. So now when we come back to the screen, we're gonna see it's actually found a ton on purpose. I didn't register a ton of stuff. So we found a ton of stuff sitting out there, all these Copilots, agent cores, Amazon quick implementations, etcetera, that are out there.
