Our Why: The Gap That’s Costing You

Your competitors are about to make decisions faster than you can hold a meeting.

You’ve built the dashboards. Deployed the sensors. Achieved “peak insight.” But when conditions change — a wildfire shifts, a supply chain breaks, a grid fails — you’re still too slow.

The gap isn’t data. It’s the time between seeing a problem and acting on it. We call this Decision Latency — and it’s costing most operations $50K–$500K per quarter.

SpatialNext is a research lab studying how to close it. We’re selecting partners for our 2026 research cohort.

See how it works below.

What We Deliver: The Decision Velocity Diagnostic

We’re not selling software. We’re not a consultancy. We’re a research lab — and we’re looking for partners.

We’re building the definitive framework for Decision Velocity: how organizations move from insight to action. To validate it, we need real operational data. In exchange, we give you a diagnostic most firms would charge $15K for.

What you receive:

  • Your Latency Score — where your decisions slow down and why
  • Your Latency Tax — the dollar cost of hesitation, calculated
  • An Architecture Map — where World Models and Reasoning Engines fit in your stack
  • A Vendor Shortlist — 3 technologies matched to your specific bottleneck

What we need from you:

  • 2 hours of your time (one intake call, one readout — 4 weeks apart)
  • 3 examples of decisions that were too slow
  • Anonymized process documentation (no system access required)

What we keep:

The right to use anonymized patterns in our 2026 State of Decision Velocity Report

This is collaborative research, not consulting. We’re selecting 3–5 partners per quarter.

Apply for the Research Cohort

Who This Is For

We work with senior leaders who own high-stakes decisions — where delay means losses.

You’re a fit if:

  • You own decisions where hesitation has a measurable cost (dollars, time, safety, mission)
  • You’ve invested in data and dashboards — but still feel too slow when conditions change
  • You’re a senior operator, not a student or researcher
  • You’re willing to share anonymized workflow examples for our research

You’re not a fit if:

  • You’re looking for a vendor to build software (we diagnose, we don’t implement)
  • You need a proposal you can hand to procurement (this isn’t a sales process)
  • You’re early-stage or pre-revenue (we need real operational data)

We’re selecting research partners, not taking clients.

Why Now

A dashboard describes reality. A Decision Engine changes it. That’s the shift which is underway.

Three things changed in 2025:

  1. LLM reasoning got commoditized. DeepSeek matched OpenAI for 1% of the cost. The “chatbot” layer is now table stakes — not a differentiator.
  2. The smart money moved beyond LLMs. Bezos, Fei-Fei Li, and Yann LeCun are betting on World Models — systems that simulate what-if in the physical world, not just generate text.
  3. The real competition moved up the stack. The question is no longer “Do we have AI?” It’s “Do we have a second brain in the room — one that reasons to what-next faster than theirs?”

The 18-month window is open.

The organizations that master Decision Velocity now won’t just have an advantage — they’ll set the tempo for their entire industry.

The rest will be explaining to their boards why they’re still paying people to stare at screens.

Apply for the 2026 Research Cohort

Blog

  • Beyond the Hype: Why 2026 is the Year of the Physical AI Revolution

    Beyond the Hype: Why 2026 is the Year of the Physical AI Revolution

    Author: Matt Sheehan The “adults in the room” of AI research are quietly pivoting away from pure LLMs. Here is the new stack—World Models, Causal AI, and Decision Engines—that will define the next phase of intelligence. If you are reading this, you are likely suffering from the same affliction as the rest of us: AI…

    Read more

  • From LLMs to World Models: How Causal and Agentic AI Will Run the Next Wave of Decisions

    From LLMs to World Models: How Causal and Agentic AI Will Run the Next Wave of Decisions

    Summary: Large language models (LLMs) are just the interface layer. The next wave of AI combines world models for simulation, causal AI for understanding cause and effect, and agentic decision engines that take action. This guide explains how these four layers work together to transform operations in logistics, finance, emergency response, and industrial settings. Key…

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  • Beyond the Chatbot: Why World Understanding Is the Next Decision Frontier

    Beyond the Chatbot: Why World Understanding Is the Next Decision Frontier

    By Matt Sheehan, Spatial-Next AI is in the middle of a quiet but profound transformation. This week, research labs, hardware manufacturers, and enterprise executives all pointed toward the same realization: large language models (LLMs) have reached the limits of language. The next breakthrough is world understanding — the foundation of true decision intelligence. From Judea Pearl’s remarks on…

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  • Why your modern platform is built for yesterday’s bottleneck—and what comes next.

    Why your modern platform is built for yesterday’s bottleneck—and what comes next.

    Most organizations are stuck at Stage 2 of AI maturity. Here’s the five-stage journey to anticipatory intelligence—and why your architecture determines how far you can go. Key Takeaways Why AI Dashboards Aren’t Enough There’s a quiet conversation happening in boardrooms and operational HQs right now. It sounds something like this: “We’ve invested in the platform.…

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  • Beyond the Chatbot: Why Human Judgment Is the Operating System for Decision Intelligence

    Beyond the Chatbot: Why Human Judgment Is the Operating System for Decision Intelligence

    The Executive Summary The 55% Reality Check For the last three years, the AI narrative has been about automation, efficiency, and removing friction. The implicit promise: AI will decide so you don’t have to. This week, the data told a different story. A joint report from Nasscom and Indeed, analyzed in ET Edge Insights, revealed…

    Read more

  • The Grounding Layer: Why Spatial Intelligence Is the Missing Piece of the Decision Stack

    The Grounding Layer: Why Spatial Intelligence Is the Missing Piece of the Decision Stack

    Decision Layer Signal Scan: January 12, 2026 Published: January 12, 2026 | Read Time: 7 minutes TL;DR: Physical AI investment hit $10.3 billion in 2025—up 61% year-over-year. Industry analysts are calling 3D World Models the “ImageNet moment” for robotics. And new research reveals why LLMs will never be enough: they lack grounding in physical reality.…

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  • The Pivot to Physical AI: Why NVIDIA Just Validated the Decision Layer

    The Pivot to Physical AI: Why NVIDIA Just Validated the Decision Layer

    The Decision Layer Era: Why Decision Velocity Is the New Competitive Advantage in AI The chatbot era is ending. The companies winning in 2026 are building for reasoning, simulation, and action—not conversation. What Is the Decision Layer? The Decision Layer represents a fundamental shift in enterprise AI architecture. Rather than systems that describe problems (chatbots),…

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  • The Chatbot Era Is Over: Hardware, Research, and Capital All Point the Same Direction

    The Chatbot Era Is Over: Hardware, Research, and Capital All Point the Same Direction

    Decision Layer Signal Scan: January 5, 2026 Published: January 5, 2026 | Read Time: 7 minutes TL;DR: NVIDIA just built hardware explicitly for World Models. TechCrunch declared 2026 the year AI moves from hype to pragmatism. Google’s Genie 3 is being called the “GPT-3 moment” for interactive environments. The signals from this week all point…

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  • What is Decision Latency? The Hidden Cost Killing Your Operations

    What is Decision Latency? The Hidden Cost Killing Your Operations

    By Matt Sheehan, Decision Architect Matt Sheehan helps organizations close the gap between insight and action. He publishes The Augmented Decision-Making Brief, a weekly newsletter tracking the shift from dashboards to reasoning engines. Key Takeaways What is Decision Latency? Decision Latency is the gap between when data becomes available and when action is taken. Here’s…

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  • Your Competitor Just Got a $500 Million Head Start for $6 Million

    Your Competitor Just Got a $500 Million Head Start for $6 Million

    Decision Layer Signal Scan: December 29, 2025 Published: December 29, 2025 | Read Time: 6 minutes TL;DR: DeepSeek made the thinking layer cheap. Now the competition moves up the stack. The $6 million revolution didn’t just change AI economics—it eliminated the last excuse for waiting. Meanwhile, 95% of enterprise AI pilots are failing, and it’s…

    Read more

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