Kalanithi
Construction has never lacked data. What it has lacked is clarity.
Today’s jobsites generate enormous volumes of information — drawings, schedules, RFIs, reports — but much of what truly matters still lives in the physical world: what was actually installed, where work stands right now, and how jobsite conditions are changing day by day. As projects grow more complex and labor becomes harder to find, the gap between what teams think is happening and what’s actually happening on-site has become one of the industry’s biggest sources of risk. That gap is why visual intelligence is emerging as the next major shift in construction technology.
Visual intelligence represents a move beyond traditional reality capture. For years, photos, videos, and 360° imagery have helped teams document their job sites. But documentation alone doesn’t scale, and it doesn’t solve the real problem. The next step is systems that can automatically organize, understand, and act on visual data, turning raw imagery into usable intelligence that fits naturally into how builders work.
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At its core, visual intelligence is powered by spatial AI: artificial intelligence models trained not just on images, but on physical context. These systems understand location, sequence, and relationships between building elements. They can recognize materials, associate images with 3D building information models and floor plans, and track progress over time. Instead of scrolling through photo folders or relying on subjective updates, teams get a continuously updated, visual record of reality, anchored in space and time.
This shift matters because construction is still largely managed through text-based workflows that struggle to accurately reflect field conditions. Progress is debated. Percent completed is estimated. Issues surface late, often when they’re already expensive. Visual intelligence introduces an image-first approach that aligns digital systems with how builders naturally assess work: by looking.
In practice, this means imagery can now drive decisions rather than merely support them. Automated capture — using smartphones, 360° cameras, and drones — creates a complete visual history of the jobsite without burdening field teams. AI then pins every image to the correct location, compares progress week over week, and highlights where work is advancing, stalling, or deviating from plan. That intelligence flows directly into workflows like progress validation, QA/QC, coordination, and billing.
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The impact is tangible. On large, complex projects, teams are identifying productivity issues far earlier — sometimes at 10% completion instead of 50% — dramatically reducing downstream cost exposure. Owners and executives gain reliable visibility across portfolios without constant site visits. Project teams save hours previously spent walking sites, collecting photos, and manually compiling reports, freeing them to focus on coordination and problem-solving instead of data collection.
Importantly, this is not about replacing human judgment. Construction progress remains highly variable and difficult to automate fully. The most effective visual intelligence systems combine AI with human expertise — using trained professionals to validate outputs, refine models, and ensure accuracy. This human-in-the-loop approach delivers results that teams trust, while allowing AI to scale what people alone cannot.
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As visual intelligence platforms mature, their value compounds. Each captured image adds context. Each verified data point improves the underlying models. Over time, systems become more predictive, more autonomous, and more capable of surfacing risk before it turns into rework or delay. The result is not just better documentation, but a more reliable operating picture for the entire project team.
The construction industry is under pressure to build faster, safer, and with fewer resources. Meeting that challenge will require tools that reflect reality, not abstractions. Visual Intelligence does exactly that by grounding digital workflows in what’s actually happening on-site.
We’ve spent decades managing construction through reports and recollection. The next era will be managed through continuously updated visual truth. For builders navigating increasing complexity, that shift isn’t just helpful — it’s necessary.
Jeevan Kalanithi is co-founder and chief executive Officer of OpenSpace in San Francisco, a visual intelligence platform for contractors. Prior to starting OpenSpace, Jeevan served as entrepreneur-in-residence at Lux Capital. He sold his first company, Sifteo, to 3D Robotics, where he eventually became the company’s president.
