The Value of a Data Intelligence Cloud for Oil & Gas Part 1: Production Optimization
It should be no surprise that AI transformation of the Oil & Gas industry will require big investments. Technavio reported that “Digital...
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Where everyone can visualize the feature and predict step.
Where everyone can visualize the feature and predict step.
It should be no secret that corporate productivity is directly tied to getting the right information to the right person and the right time in a format that they can understand and use. But, how often have you been a meeting where the business executives are asking IT for something but all of the other stakeholder’s opinions on what they really want gets in the way of delivery of the actual product requested?
Compound this problem with the natural communication gap between executives “business speak” and the “technical speak” of the IT department and you have a recipe for chaos.
There is a classic story dating back to the 1970’s of how a product comes to market through the lens of the individual stakeholders using a tree swing analogy for why project management usually goes awry: The customer asks for a swing. A large group of people plan, align, review, and re-scope. Something is finally built after months and months. And… no one swings on it. The question we’re hearing across right now is how do we move faster?
The truth is, we’ve already made development faster. GenAI and modern tools have shortened the time from idea to prototype. That’s not the bottleneck anymore. The bottleneck is everything around the build: – The layers of translation – The “alignment” cycles – The assumption that if we just plan it right, we’ll get it perfect.
Spoiler: we won’t. Because the plan isn’t the product. The product is the product.
And if we don’t show it to our users until it’s “done,” we’re guaranteed to miss. So, here’s what we need to tell teams: Put the engineer and the business partner in the same room. Not metaphorically. Literally. Let them hear the customer’s pain. Let them ask questions. Let them build the first version in real time. It won’t be perfect. That’s the point. Show it early. Make changes while it’s still easy. And make someone single-threaded on the outcome. Because even though we work in a four-in-the-box model, every mission still needs a clear driver. We’re not in a world where we can afford to wait months to be wrong. We have to be wrong faster, so we can get to right sooner. Where are you seeing speed happen in your org? And what’s still getting in the way?
In traditional software and AI projects, building a solution often feels like that swing cartoon—where every team sees the problem differently and the final result misses the mark. The customer describes one thing, the project lead hears another, and by the time it's built, supported, and billed, it's nowhere near what was really needed.
UBIX flips that model.
With our no-code AI platform, business users aren’t sidelined—they’re empowered to be hands-on with a data intelligence cloud. They can start by exploring or modifying a visual model that already exists or even sketch out a first-of-a-kind prototype on their own. This gives data scientists a concrete foundation to enhance, rather than starting from a blank slate.
The result? Business and IT work in lockstep, not in silos. Miscommunication is replaced by shared understanding. Iteration happens faster. Models are more relevant, and outcomes more aligned to real business needs.
UBIX bridges the gap—so what gets built is what’s actually needed, the first time.
Stage |
Before UBIX (Traditional AI) |
With UBIX (No-Code AI) |
How it starts |
Business describes a need, which gets filtered through layers of interpretation |
Business user builds or modifies a visual model directly in UBIX |
Role of data scientist |
Works separately to design and build the model, often with limited business context |
Collaborates early to enhance and operationalize a prototype the business helped shape |
Development process |
Long alignment cycles, miscommunications, siloed workstreams |
Shared workspace, fast iterations, continuous feedback |
Time to first version |
Weeks or months |
Hours or days |
Level of rework |
High – business sees the product late and often requests major changes |
Low – business sees and shapes the product from day one |
Outcome |
Overbuilt, underused solution – no one "swings on it" |
Fit-for-purpose solution – exactly what was needed and used |
Team dynamic |
Handoff-driven, plan-heavy |
Collaborative, outcome-driven |
Result |
Wrong solution delivered too late |
Right solution delivered faster |
Learning how GenAI and emerging advancements like Reinforcement Learning and AgenticAI can deliver on the promise of a data intelligence cloud for increasing levels of autonomy and enterprise impact. Download our free eBook titled “5 Steps to AI Business Transformation Success” to help better understand the nuances of emerging AI concepts and technologies and offer a set of best practices for consideration to ensure digital transformation and business-led AI success. Or if you can spare 22 minutes for a mini–AgenticAI Readiness Workshop, you can contact one of our AI experts today.
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