Mapping America's Invisible Dangers: AI Tackles Buried Utility Crisis

AUSTIN, TX – August 11, 2026

Today is 8/11, a date designated to remind every contractor, developer, and homeowner to “Call 811” before digging. It’s a simple, crucial message aimed at preventing catastrophic damage to the vast, invisible network of utilities beneath our feet. But for Itzik Malka, CEO of the tech firm 4M, this annual reminder highlights a deeper, systemic failure. “A utility strike is not an accident,” Malka declared in a statement today. “It is almost always the predictable outcome of making critical decisions without accurate knowledge of what lies underground.”

This provocative statement challenges a long-held industry narrative. Yet, the data supports a grim picture. In the past year alone, the U.S. saw over 213,000 documented utility strikes, a figure that industry watchdogs like the Common Ground Alliance (CGA) suggest may represent only a fraction of the actual total. These incidents are not mere inconveniences; they have led to home explosions, tragic deaths, and environmental disasters, costing the U.S. economy an estimated $30 billion annually, before even accounting for project delays and indirect costs.

The core of the problem lies buried with the infrastructure itself: the records for the 50 million miles of pipes, cables, and conduits crisscrossing the nation are a chaotic patchwork of outdated blueprints, inaccurate digital files, and forgotten assets. For decades, the industry has relied on a reactive system of physical line-marking that is often a best-guess effort. 4M Analytics is betting that artificial intelligence can finally provide the solution that decades of policy and practice could not.

The High Cost of an Invisible Problem

The current “Call 811” system, while essential, is fundamentally a last-minute defense. It’s a process that begins only after a project has been designed, funded, and is ready to break ground. An excavator calls the one-call center, which then notifies local utilities to dispatch technicians who use spray paint and flags to mark the approximate location of their lines. The key word is approximate.

“The system is built on fragmented, often analog-era data,” explains a senior civil engineer who has spent decades navigating infrastructure projects. “You have utilities with records on paper maps from the 1970s, others with incomplete GIS data, and countless ‘ghost’ pipes that were never documented at all. The locator technician is doing their best, but they can only mark what’s in their records, and those records are often wrong.”

This data deficit has staggering consequences. According to data from the Pipeline and Hazardous Materials Safety Administration (PHMSA), excavation damage remains a leading cause of serious pipeline incidents. The CGA’s 2023 DIRT Report, which analyzes damage data, paints a similar picture, linking strikes to fatalities, injuries, and widespread service disruptions. The problem isn’t a lack of effort, but a lack of reliable, comprehensive information at the most critical stage: project planning.

A Digital X-Ray for the Nation

4M Analytics proposes to solve this by creating what it calls “America's Subsurface Model”—a live, unified map of infrastructure both above and below ground, spanning all 50 states. The company, founded in 2019 and backed by prominent investors like Insight Partners and Waze’s former CEO Noam Bardin, is not relying on shovels or ground-penetrating radar. Instead, its primary tool is a proprietary, deterministic AI.

This AI platform acts as a massive-scale digital detective. It ingests and analyzes a vast array of visual data—from street-level and aerial imagery to public records and satellite feeds. It’s trained to recognize the subtle clues that hint at what lies beneath: the placement of a manhole cover, faint trench lines visible only from the air, or the specific markings on a utility pole. By cross-referencing these visual indicators with network topology principles and engineering logic, the system can generate lines for undocumented utilities and, crucially, identify and correct errors in existing records.

This approach represents a paradigm shift from traditional Subsurface Utility Engineering (SUE), which relies on sending crews to physically map small project areas. While effective, these methods are expensive, time-consuming, and not scalable to a national level. 4M’s AI-driven strategy aims to provide that scale, delivering reliable data directly into the CAD and GIS platforms that engineering teams at firms like WSP, Stantec, and AtkinsRéalis already use. The company is on track to complete its map of all 50 states by the end of 2026, creating a foundational layer of intelligence for the entire infrastructure sector.

From Blueprint to Reality: Putting Data to Work

The true value of this technology lies in its application early in the project lifecycle. With access to a comprehensive subsurface map during the design and bidding phases, engineering firms can route new infrastructure to avoid conflicts, reducing the need for costly and time-consuming redesigns. Contractors can bid on projects with greater confidence, minimizing the risk of unexpected underground obstacles that can derail timelines and budgets.

This shift to proactive, data-driven planning is arriving at a critical moment. The Infrastructure Investment and Jobs Act (IIJA) has unlocked unprecedented funding for modernizing America’s roads, bridges, and utilities. Maximizing the impact of this investment requires building more efficiently and safely than ever before. “Knowing what’s underground before you even start designing is a complete game-changer,” notes one industry analyst. “It moves risk from an unknown variable to a manageable constraint.”

Furthermore, this technology is a key enabler for the development of “digital twins”—virtual replicas of physical assets and cities. A true digital twin must include the complex web of subsurface utilities to be effective for urban planning, emergency response, and long-term maintenance. By providing this missing data layer, platforms like 4M’s are laying the groundwork for more resilient and intelligently managed cities.

The company points to its data’s potential to have offered critical insights in recent incidents, such as a reported crude oil spill in Los Angeles caused by a fiber optic installation and a large natural gas leak in North Carolina. By having a complete picture beforehand, planners and crews can identify high-consequence areas and take preventative measures.

Redefining Prevention for a New Era

The ultimate vision is to evolve beyond “Call Before You Dig” to a new standard: “Know Before You Design.” While the 811 system will remain a vital safety check, supplementing it with a reliable, comprehensive data source fundamentally changes the equation. It transforms damage prevention from a reactive, last-ditch effort into a proactive, integrated part of the entire infrastructure lifecycle.

This shift has profound implications for risk management, insurance, and regulation. As this technology proves its ability to reduce strikes, it could influence future policy, potentially creating new standards for data accuracy and sharing among utility owners and constructors. For the men and women working in the trenches, it promises a safer work environment where the ground beneath their feet is no longer a dangerous unknown.

By building a unified map from a mosaic of fragmented data, 4M Analytics is not just selling a product; it’s proposing a new national infrastructure for intelligence, one that could finally bring the hidden world of utilities into the light.