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SPOTLIGHT

LLMs vs PFNs: Why ChatGPT-style AI Struggles with Spreadsheets.

LLMs taught us something useful: knowing language isn't the same as learning from data. They can read a table, but as columns grow they struggle, their wins on famous datasets are often memory, and harmless changes shift their answers. PFNs were built for exactly the job LLMs find hard. They practise on endless synthetic tables until learning from a table is second nature, and it shows: top accuracy on small-to-medium datasets, answers in seconds, and results that stay put. The lesson is simple: use LLMs for words and code, and use PFNs like TabPFN when you need predictions from tables.

Blogs

Digitizing Intuition with SME-Agents

Over the past decade, leaders, industries, and vendors have championed the shift to data-driven decision-making. Yet the reality remains: data is NEVER complete. Even with

Enterprise AI – Your best people are training someone else’s AI.

Building on Satya Nadella’s The Reverse Information Paradox (July 2026), and on the tabular foundation model work of Prior Labs (TabPFN). The paradox and the exhaust framing are

Foundation Models – Why Industry 4.0 Needs Its Own

Every AI model in your factory is already obsolete. Here’s why and what the next generation of industrial foundation models looks like.

How to Deliver Perfect Orders at Scale by Balancing, Not Overriding Smart Systems

Andrew’s story shows that better dashboards don’t guarantee better decisions. ProfitOps helped him go beyond siloed KPIs to orchestrated, value-driven planning. The result? Smarter trade-offs, fewer misses, and

How to Reduce Total-Cost-per-Order by Balancing, Not Overriding Smart Systems

Now, with BVI continuously monitoring trade-offs and recommending system-wide improvements, Rick doesn’t have to babysit every module. “He now has an integrated real-time adaptive decision layer.” And he’s

Digitizing Intuition with SME-Agents

Over the past decade, leaders, industries, and vendors have championed the shift to data-driven decision-making. Yet the reality remains: data is NEVER complete. Even with advanced analytics and

Part-2: Root Cause Analysis for Warehouse Automation: A Synthetic Data Exploration

In our previous post, we explored how Root Cause Analysis (RCA) can transform warehouse operations by pinpointing inefficiencies and reducing costly errors. Now, it's time to pull back

Part-2: Price and Discount Optimization: Advanced AI Process

In our previous blog post, "Evidence-Based Decision Making: Revolutionizing Pricing and Discount Strategies with Causal AI," we explored how businesses can leverage Causal AI to optimize their pricing
Optimizing Customer Order Fulfillment Costs

Optimizing Customer Order Fulfillment Costs: A Practical Approach Using AI

In today’s competitive supply chain landscape, minimizing fulfillment costs is crucial. This blog explores how fulfillment cost optimization can be achieved using linear programming with tools like Google

Case Study: Root Cause Analysis in Warehouse Automation using Causal AI

In today’s fast-paced industries, especially in complex environments like warehouse management, it’s critical to understand how different factors influence key outcomes. For example, in a warehouse setting, packages
Evidence-Based Decision Making

Part-1: Evidence-Based Decision Making: Revolutionizing Pricing and Discount Strategies with Causal AI

In the fast-evolving business landscape, making decisions based on intuition is no longer enough. Pricing and discount strategies are two of the most crucial factors that directly influence