Operational Ontology

Bringing Operational Science and Data Science together...

Imagine you're trying to solve a giant jigsaw puzzle, but instead of one person working on it, you've got a hundred people, each with their own pieces, and no one knows what the final picture is supposed to look like. This is what companies face with big data – lots of information, but it's scattered, siloed, and making sense of it all seems nearly impossible. That's where Palantir's ontology steps in, and no, it's not something out of a medical textbook. It's far from it.

Ontology, in the world of Palantir, is like the game plan for organizing all these puzzle pieces. It's not just another piece of tech; it's a revolutionary approach to understanding and connecting data. Here's the kicker: unlike past technologies that just piled data higher and deeper, Palantir's ontology lays out a map. This map tells us how different pieces of data relate to each other, making it easier to see the big picture – whether that's predicting market trends, optimizing supply chains, or even preventing fraud.

The power of operational transformation

The challenge in reaching unprecedented levels of operational efficiency has always been our inability to view our source data through a genuine and precise "operational lens." To demonstrate the transformation of various data sources into a singular operational entity, let's consider the example of a manufacturing plant, highlighted by the blue box below.

Beneath, you'll find other boxes representing a diverse array of data sources, all of which converge to form a unified operational entity - our manufacturing plant. These sources encompass:

As evident, constructing an authentic operational image of the manufacturing plant necessitates integration from multiple data sources. Furthermore, to elevate these data sources for optimal use at the level of operational ontology, certain sources undergo a transformative process, as indicated by the green boxes on the diagram below.

This endeavor demands considerable strategic thought and preparation, yet the rewards are substantial. It marks the beginning of viewing our organization through a genuine "operational lens," as opposed to the challenging, often insurmountable task of attempting to discern and refine operations relying solely on disparate data sources.

Data Transformation

Palantir uses "data transformation" for not only data integration (although it is used for that), but to create true "operational objects" that relate directly to the operational optimization process.

Below we see multiple data sources being abstracted into a single "operational object", in this case the manufacturing plant. It is this "operational object" that sits within the operational ontology provided by Foundry.

So, why is this such a game-changer?

Because for the first time, it feels like we're not just reacting to data, we're anticipating it. We're making connections we couldn't see before, and that's leading to breakthroughs in efficiency, decision-making, and innovation. It's like we've been given a new lens to look at our data, and suddenly everything clicks into place.

But here's why it's really different – it's not just about connecting dots. It's about doing so in a way that's tailored to the unique needs of each customer. Traditional tech solutions often come with a one-size-fits-all approach, but Palantir's ontology is more like a custom suit, designed to fit the exact contours of a business's challenges and opportunities.

And the results?

They speak for themselves. Companies are not just solving problems faster; they're solving problems they didn't even know they had. They're uncovering opportunities hidden in plain sight. And in today's world, where data is the new gold, being able to mine it more efficiently and effectively than ever before doesn't just give companies an edge – it's setting a new standard for what's possible.

In essence, Palantir's ontology is rewriting the rulebook on data management and utilization. It's not about bombarding you with more information; it's about making all that information work smarter, not harder. And in doing so, it's transforming industries, one insight at a time.

How it Works

Connect AI to Construction
with Project Data

The Ontology (a set of concepts that shows properties and the relations between them) integrates real-time data from all relevant sources into a semantic model of the business.

This anchors AI in the operational truth of the enterprise, mitigating the risk of model hallucinations and creating the trust needed for decision-making.

Connect AI to Construction
with Project Logic

The Ontology binds AI to the traditional business logic, models, optimizers, and other computations that are spread across environments and power enterprise processes.

Permitted logic assets become deterministic tools that complement AI-driven reasoning and decisioning.

Connect AI to Construction
with Project Action

The Ontology enables AI to safely synchronize decisions back to operational databases, edge platforms, and other systems of action. AI-authored proposals can be subject to human validation.

Scenarios can be generated and examined for potential impact. All action can be audited.