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Most teams today rely on dashboards, spreadsheets, and scattered reports to make sense of their business. They have data, but not clarity. Before getting into the story, it helps to anchor two simple ideas:
An AI Analyst is software that reads your data, keeps your context, and explains why numbers shift in a way that feels like talking to your best analyst.
A Decision Intelligence Platform is a system that connects your data, logic, and business rules so you can ask questions in plain English and get answers you can use.
With that foundation, let’s get into the world you’re already living in.
Picture this: It's 4 PM on a Tuesday. You're in a strategy meeting, and someone asks, "Why did our Q2 numbers drop?" Everyone looks at the analyst. The analyst looks at their laptop. And you all know what comes next: "Let me pull the data and get back to you by Friday."
Sound familiar?
Every professional today faces the same impossible choice: speed or depth. You either rush through the analysis and miss the nuances, or you dig deep and miss the deadline. Rarely can you do both.
Half of every professional's day disappears into spreadsheets and slide decks. Not doing strategy. Not making decisions. Just trying to connect numbers that refuse to live in the same place.
Your best people are stuck being data plumbers. Whether they sit in Sales, Product, Finance, or Marketing, they spend more time wrangling data than thinking critically or moving the business forward.
Outsourcing doesn't help. By the time an external team “figures out” your context, the landscape has already shifted.
Because the data you need already exists — it’s just fractured.
Revenue in one file.
Customer behavior in another.
CRM in one system.
Campaign data somewhere else.
Finance has its own truth.
None of these sources talk to one another.
Teams are drowning in information but starving for answers. Reports from McKinsey reinforce this, noting that a majority of companies sit on scattered data with little to show for it. And while BI tools promised clarity, Gartner’s finding that fewer than 35 percent of employees open dashboards weekly tells you exactly how far that promise went.
A typical workflow today looks like this:
And still no explanation of why something happened — only what happened.
Then came the AI wave. Everyone thought tools like ChatGPT could finally help teams “talk to their data.” But these systems were built to write, not to reason. They look at the first few dozen rows, draw shallow patterns, and miss the relationships that drive business outcomes. And they weren’t built to run inside your systems securely.
So we built Green to close the distance between what teams see and what they understand.
Before we wrote a line of code, we asked a simple question:
What if every professional had an analyst who never forgot anything about their business?
Think about your best analyst.
The one who remembers how you define pipeline.
The one who recalls why last year’s Q3 spike happened.
The one who knows the subtle differences between “leads” in Marketing and “leads” in Sales.
Now imagine that analyst never took a day off, never forgot a metric, and got sharper with every question you asked.
You talk to Green the way you talk to your analyst:
Green reads across your spreadsheets, slide decks, and notes together.
It understands how your data points relate.
It uses a living map (ontology) of how your business works.
It performs real numerical reasoning instead of guessing.
It remembers your definitions, your history, and how your teams think.
Every answer shows its working — the logic, the data, the steps.
Your information stays in your environment, private and controlled.
Over time, Green learns how your business works.It remembers how you define metrics, how your systems connect, and which signals matter most.This is where context-aware reasoning becomes powerful because Green starts understanding what makes your decisions unique.
This table blends naturally with the story and helps readers place Green without feeling like a comparison ad:
It’s not about charts or paragraphs. It’s about understanding.
| System | What It Shows | What It Misses |
|---|---|---|
| Dashboards | Past activity | The reasoning behind it |
| Language models (ChatGPT, Claude, Gemini etc.) | Text output | Numerical logic and context |
| Green | Relationships and explanations | Designed for decisions |
Remember the 50 percent of your week you lose to Excel, PowerPoint, and data gathering?
Green gives that time back.
Here’s what actually changes:
Green’s value compounds.
It learns your priorities.
It adapts to how your team interprets signals.
It grows with every question you ask.
This isn’t about replacing judgment.
It’s about giving you the space to use it.
Less time hunting.
More time understanding.
That’s how teams move from slow, foggy decisions to clear, confident choices.
Question: “Why did Q2 bookings fall?”
A dashboard shows the decline.
A generic model writes a paragraph.
Green connects the dots.
Green pulls sales trends, churn signals, pipeline notes, and campaign activity into one view.
It can spot timing gaps, weak funnel stages, or a churn bump in specific segments — then shows how it reached the explanation.
This type of reasoning used to take days.
Now it happens in seconds.
A decision intelligence platform helps you ask questions in plain English and get clear reasoning.
Green does this by:
It works the way your business works — not the way tools expect it to work.
Green is live now.
If you're tired of tools that tell you what happened but never explain why it matters, Green is ready for you.
If you're done spending half your week preparing decks instead of making decisions, Green was built for exactly that moment.
Green is an AI analyst that learns from every conversation and explains the reasoning behind your data. It connects information across spreadsheets, slides, and reports to answer "why" questions, not just "what" questions.
Green uses a living ontology to understand your specific business context and does real numerical reasoning. Unlike language models that treat numbers like words, Green is built specifically for analytical reasoning and actually remembers how your business works.
Yes. Green is built Enterprise Grade with best-in-class Data security Architecture.
Anyone who spends significant time in Excel and PowerPoint hunting for insights. Leaders who need fast answers without sacrificing depth. Analysts who are tired of being data plumbers. Teams that want to move faster without moving recklessly.
No. Green handles the repetitive data work so your analysts can focus on what only humans can do: strategic thinking, business judgment, and driving impact.
Ranjan Kumar, Founder & CEO, DecisionX
Ranjan Kumar is the Founder and CEO of DecisionX AI, the world’s first self-learning, context-aware Decision Intelligence platform that enables enterprises to make smarter, faster business decisions through agentic AI. A serial entrepreneur and three-time founder with over 17 years of experience, Ranjan previously built Entropik, the world’s first Emotion AI platform with 17 global patent claims. An IIT Kharagpur alumnus, he is widely recognized as a thought leader in enterprise AI, Ontology Engineering, decision reasoning, and AI-driven business transformation.
