OpenSpace construction AI—spatial computing & generative AI

Michael Fleischman is the Chief Technology Officer and Co-Founder at OpenSpace

Introduction: a moment of convergence

AI has captured the public’s imagination in ways we haven’t seen before. Whether it’s breakthroughs in large language models or the latest in robotics, artificial intelligence is becoming part of everyday conversations—and not just in tech circles.

But why now?

What we’re seeing is the result of two major trends coming together: spatial computing and generative AI. At OpenSpace, we’ve been building at this intersection for years, and we call it the OpenSpace Spatial AI Engine—the core intelligence that powers many of our most advanced features.

This post takes you under the hood of Spatial AI: what it is, why it matters, and how it’s shaping the future of construction technology.

A brief history of AI hype—and substance

The term artificial intelligence has been around since the 1950s, and interest has come and gone in waves. Occasionally that interest spiked—often aligned with pop culture moments, like the release of 2001: A Space Odyssey in 1968 and The Terminator in 1986.

Despite those early surges, most of AI’s history was relatively quiet in terms of popular impact. There were impressive milestones—like IBM’s Deep Blue defeating chess grandmaster Garry Kasparov in 1996 or Watson winning at Jeopardy!—but these were isolated demonstrations, not the world of the Jetsons that we were promised.

What’s changed in the last decade is the combination of computing power, data availability, and algorithmic sophistication. AI is now more than a lab curiosity—it’s finally moving out of the world of pure science fiction to becoming a practical tool across industries.

Spatial computing: bringing AI into the physical world

At its core, spatial computing refers to systems that understand and interact with the physical environment. The term dates back to the 1980s, but in recent years it’s taken on new meaning, thanks to applications like:

• Virtual and augmented reality (e.g., Apple Vision Pro)
• Self-driving cars (e.g., Waymo)
• Robotics (e.g., Spot from Boston Dynamics) and drones
• Air quality prediction (e.g., PurpleAir Sensors)

While companies like Apple have rebranded spatial computing around immersive experiences (in fact Apple insists that their VR products be called “Spatial Computing”), the concept is much broader. It’s about enabling machines to navigate, perceive, and reason about the world around them.

At OpenSpace, we saw this trend on the rise and further believed that as sensors (especially cameras) became smaller, cheaper, and more powerful, there would be an opportunity to bring spatial computing to construction. By combining these sensors with techniques like SLAM (Simultaneous Localization and Mapping) and Structure from Motion, we could automate site documentation and make jobsite data more accessible than ever before.

That idea became the foundation for OpenSpace, and to date, our users have captured more than 40 billion square feet of jobsite imagery.

The rise of generative AI

At the same time, another transformation has been unfolding: the rise of generative AI. These are systems that can create content—text, images, audio, video—based on learned patterns from massive datasets.

These generative models power a new class of AI chatbots, ChatGPT being the most well-known example, which are far more capable than previous generations of chatbots like Siri and Alexa (let alone the generation before, most infamously known for examples like Microsoft’s Clippy).

Why is this all happening now?

The key breakthrough was a machine learning architecture called the transformer, which enabled large-scale models to be trained across many machines in parallel. This allowed systems to process vastly more data than ever before.

The resulting foundation models learned to do something deceptively simple: predict the next word in a sentence. But in doing so, they absorbed not just grammar and facts, but also common-sense knowledge about how the world works.

For instance, they can “understand” that if you drop a bottle of water, it might spill—and that spilled water could be slippery. This kind of contextual awareness was notoriously difficult to teach machines in earlier eras of AI.

While such foundation models are powerful, they’re not enough on their own. To make them useful for specific industries or tasks, they need fine-tuning—a process that involves exposing the model to curated examples, often with human feedback.

This is where generative AI becomes practical. Fine-tuned models can perform specialized tasks like summarizing reports and answering questions—if they’re trained properly and grounded in domain knowledge.

But without that tuning, these models can feel vague or generic. As DPR Construction highlighted in a recent report, general-purpose AI tools often fall short when applied to real-world construction scenarios. They’re not always wrong, but they’re rarely insightful.

Introducing the Spatial AI Engine

At OpenSpace, we’re solving that problem by combining the strengths of each world:

• Spatial computing for understanding physical environments
• Generative AI for understanding language and context
• Domain-specific tuning for real construction tasks

This fusion powers our Spatial AI Engine—a system that can interpret 360° imagery, mobile photos, documents, and even natural language instructions to help users navigate complex jobsites.

Looking ahead: AI that works for you

The goal of Spatial AI isn’t just to make technology smarter—it’s to make your work easier, faster, and more informed. That’s why we’re building systems at OpenSpace that are tuned specifically for construction, trained on real data, and designed to integrate seamlessly into existing workflows.

This is just the beginning. As the technologies behind spatial computing and generative AI continue to evolve, so will our ability to turn them into practical, impactful tools for the built world.

Related resources:

• Michael Fleischman’s Waypoint 2024 talk on spatial computing and generative AI
• OpenSpace Spatial AI Engine overview
• Explore a real OpenSpace project to see our AI tech in action