Getting Real Value from Enterprise Data Means Reimagining How Teams Work Together

How Conode AI Makes Graph-Powered Intelligence Accessible to Any Team

In any data-rich enterprise—be it an insurance giant, a manufacturing powerhouse, or a global supply chain operator—there’s an invisible divide holding teams back: data is owned by some, but needed by all.

On one side, you have the data professionals—data scientists, engineers, analysts—who know how to structure, query, and validate. On the other, business experts—underwriters, actuaries, product managers, compliance officers—who hold the domain expertise but are too often blocked by tools they can’t use or dashboards they didn’t design.

In between? A bottleneck.

One that slows decisions, obscures insights, and fractures collaboration.

When Everyone Needs Data, But No One Can Get to It Together

Across industries, the problem is the same: the people who need answers aren’t the ones who own the data—and the people who own the data are overwhelmed by constant requests for insight.

• A compliance officer needs to trace a policy’s history—but depends on IT to locate documents.

• A supply chain analyst wants to identify supplier risks—but struggles to connect part-level data from multiple systems.

• A product manager asks for trends across customer feedback—but is told to wait for the next dashboard refresh.

• A data scientist is pulled away from core modeling work to “just grab one more report.”

  
  

These teams are working from the same data, but in different tools, languages, and mental models. Even with BI dashboards and self-service platforms, the divide persists.

Why?

Because dashboards don’t explain why. SQL doesn’t explain how. And AI that hallucinates is more dangerous than helpful.

What’s Missing: A Shared Language for Shared Data

The problem isn’t just technical—it’s human.

To collaborate effectively around data, teams need a shared mental model, a common language, and a system that makes it safe to ask hard questions—even if you don’t know how to code.

That’s where Conode comes in.

Conode: A Collaborative Knowledge Graph for Real Work

Conode transforms fragmented enterprise data into a dynamic, explainable knowledge graph that both technical and non-technical users can interact with—using plain language, not code.

It does three things that change the game for collaboration:

1. Fuses complex data into a shared structure

   Structured or unstructured. Internal or external. Conode brings it together—so underwriters and actuaries are literally seeing and querying the same context.

2. Supports natural-language interaction that’s grounded in real data

   Ask, “What are the biggest claims in Q2 across marine policies?” and get a traceable answer—not a hallucination. Even if you’ve never touched SQL.

3. Gives data teams confidence, and business teams autonomy

   Conode’s explainability means everyone knows why an answer is correct. It’s not a black box—it’s a collaborative interface into data, logic, and insight.

From Bottlenecks to Breakthroughs

In one recent deployment at a mid-sized insurer, Conode helped data scientists and claims analysts co-create a graph of policies and claims data. The result?

• Analysts could ask and answer their own questions in Slack

• Data scientists could focus on high-value modeling, not ad hoc retrieval

• Underwriters could validate assumptions with evidence—in real time

  
  

This isn’t about replacing tools. It’s about removing the barriers between people who need each other to get work done.

The Future Is Collaborative, Contextual, and Explainable

The enterprise doesn’t need more dashboards or chatbots. It needs a context layer—a place where all teams can come together, ask better questions, and find better answers.

Data is no longer just a technical problem. It’s a shared responsibility. And with the right system, it can finally be a shared advantage.

Conode is that system.

It’s not just for data people.

It’s for people who make decisions with data.