We’re taking AI-powered automation to the next level—AI-generated Data Object Graphs (DOGs) as AI Digital Twins.

The challenge? Bridging the gap between process design and execution.

Most businesses still rely on static, manually crafted workflows, making it difficult to scale, optimize, and maintain cross-domain processes. But what if AI could automatically construct and execute these workflows as dynamic, data-driven systems?

That’s exactly what we’re doing.

From Process Diagrams to AI-Generated Execution Graphs

Instead of painstakingly designing process flowcharts, we’re enabling AI to create, execute, and adapt real business processes as Data Object Graphs (DOGs).

Each node in the graph represents a concrete data product—whether it’s:
✅ A metric (e.g., Customer Lifetime Value)
✅ A dataset (e.g., transactional records from Zoho, Salesforce, etc.)
✅ A machine learning model (e.g., churn prediction, fraud detection)
✅ A GenAI model (e.g., automated insights, NLP-based recommendations)
✅ A decision model (e.g., risk scoring, credit underwriting)

These AI-generated workflows don't just describe business processes—they run them in real-time.

Example: AI-Generated Customer Lifetime Value (CLV) Model

A recent experiment involved mapping Customer Lifetime Value (CLV) as a Data Object Graph.

🚀 The AI:
1️⃣ Automatically identified the relevant data sources (e.g., CRM, transactional data, customer interactions).
2️⃣ Extracted only the necessary data, skipping the usual delays of enterprise data access and pipeline building.
3️⃣ Created an executable process that linked analytical models, customer segmentation, and predictive analytics.
4️⃣ Ran the workflow in real-time, adapting as new data entered the system.

🎯 The result?
No need for handcrafted business process diagrams—just working, explainable, AI-generated business logic.

The Big Shift: AI as Both the Architect and the Analyst

We’re seeing a fundamental shift: AI isn’t just analyzing data—it’s constructing and executing business workflows.

📌 GenAI is no longer just assisting—it’s an active agent in the business process itself.
📌 Processes aren’t static—they evolve dynamically based on real-time data.
📌 Business teams don’t need to wait for IT to model workflows—AI does it in seconds.
📌 Documentation is automated—no need for manually maintained process maps.

This means that businesses can prototype, iterate, and deploy at an insane speed.

Why This Matters

Organizations have spent decades trying to build the perfect “single source of truth”—only to realize that processes and data needs change too fast to lock things down permanently.

The AI-powered Data Object Graph approach flips the script:
🔄 Processes drive the data, not the other way around.
⚡ AI builds dynamic workflows, rather than relying on static process maps.
📊 Business and IT collaborate seamlessly, because AI is creating the execution layer in real-time.

We’re no longer designing processes first and executing later. AI designs and executes simultaneously.

The Future is Here: Who Else is Working on This?

If you’re interested in next-gen AI-driven business execution, let’s talk.

We are happy to share more details or connect with others exploring similar ideas — get in touch with us!

With Dataception's DOGs (Data Object Graphs), AI is just a walk in the park. 🐶🚀