Haven Safety AI Launches AI-Native Platform to Tackle Workplace Safety

When a serious workplace injury occurs, the aftermath follows a familiar pattern: witness interviews, scattered documents, manual data entry, and weeks of analysis before anyone understands what went wrong. For decades, this has been the standard approach to safety investigations across high-risk industries. But Joseph Hanna, co-founder and CEO of Haven Safety AI, believes there’s a better way—and he’s betting that artificial intelligence is the key to unlocking it.

“Every serious incident leaves behind a trail of signals, but today those signals are scattered across interviews, documents, and disconnected systems. We built Haven to connect those dots automatically.” — Joseph Hanna, Co-Founder and CEO of Haven Safety AI

A $160 Billion Problem with a Tech Gap

Workplace safety remains one of the most operationally critical yet technologically underserved functions inside large enterprises. Despite years of investment in reporting and compliance programs, the industry has hit a serious injury and fatality (SIF) plateau—serious incidents and fatalities persist even as organizations pour resources into traditional safety measures.

The economic toll is staggering. Workplace injuries cost the U.S. economy more than $160 billion each year, according to industry estimates. Beyond the financial impact, these incidents carry irreparable human costs that affect workers, families, and communities.

The problem isn’t a lack of data—most organizations collect vast amounts of safety information. The challenge lies in making sense of it. Traditional safety investigations generate complex, unstructured data that most organizations still analyze manually, creating delays and inconsistencies that can mean the difference between preventing the next incident and documenting the last one.

From Reactive Reporting to Proactive Prevention

Haven Safety AI officially launched this week as an AI-native platform designed to help organizations investigate incidents faster, uncover systemic risk, and prevent serious injuries before they occur. The company was co-founded in partnership with The AES Corporation (NYSE:AES), a global energy company operating in 12 countries, and AI Fund, the venture studio founded by renowned AI researcher Andrew Ng.

havenSIGHT automatically collects witness statements, processes images, and captures frontline observations through an intelligent interface that guides structured data collection.

havenEDGE analyzes incidents, surfaces causal patterns using AI, and recommends corrective actions grounded in both regulatory standards and an organization’s historical data.

havenIMPACT tracks outcomes over time and identifies leading indicators of future risk, transforming isolated incidents into predictive intelligence.

“Safety investigations are critical and their outcomes affect human lives, regulatory compliance, and organizational trust. By combining modern AI with deep domain context, the Haven team are on a trajectory to dramatically improve both the speed and quality of decision-making in high-consequence safety investigations.” — Andrew Ng, Managing General Partner at AI Fund

Real-World Validation in Energy and Beyond

The platform didn’t emerge from a vacuum. After a year and a half of building, testing, and field validation, Haven is now live and initially focused on industries with complex operations and elevated risk profiles—including energy, utilities, construction, manufacturing, and logistics.

AES Corporation, one of Haven’s co-founding partners, has been instrumental in shaping the platform through real-world deployment. The company’s Chief Product Officer and President of AES Next, Chris Shelton, sees Haven as a fundamental shift in how safety programs operate.

“We are committed to using every tool we can to see our team members home safely at the end of every workday,” Shelton said. “Haven allows our crews and safety teams to quickly digest more insights than traditional tools on the market, going from incident, to cause, to corrective actions at unprecedented speed and scale.”

The platform’s value proposition extends beyond faster investigations. By developing institutional memory over time, Haven enables predictive insights and earlier intervention—shifting the paradigm from documenting what happened to preventing what could happen next.

The Broader Implications for Industrial AI

Haven’s launch comes at a pivotal moment for AI adoption in industrial settings. While consumer-facing AI applications have captured headlines, the real transformation may be happening in less visible but higher-stakes domains—safety, operations, and risk management.

The approach Haven takes—combining structured domain knowledge with modern AI capabilities—represents a growing trend in enterprise AI. Rather than replacing human expertise, the platform augments safety teams with intelligent tools that handle data synthesis and pattern recognition while leaving critical decisions to experienced professionals.

Market observers are watching closely to see whether this model can scale across industries and geographies. The addressable market is substantial: any organization with field operations, complex machinery, or regulatory safety requirements represents a potential customer.

For now, Haven’s focus on high-risk industries with demonstrated need—energy, utilities, construction—provides a clear path to proving value before expanding into adjacent markets. The question isn’t whether AI can improve safety outcomes; Haven’s early deployments suggest it can. The real test will be whether organizations are ready to move beyond legacy approaches and embrace a fundamentally different way of managing risk.

This article was reported by the ArtificialDaily editorial team. For more information, visit Haven Safety AI and the original press release.