Zeitview, a leader in AI-driven asset intelligence for critical infrastructure, has acquired Insight M, a methane detection and analytics company serving major oil and gas operators. The acquisition marks Zeitview's entry into the oil and gas sector and expands its coverage across all key energy generation sources. Insight M uses aircraft-based methane detection to identify emissions at scale, helping operators save approximately $900 million in product value and prevent over 255 billion cubic feet of methane from entering the atmosphere. The company serves clients including Occidental Petroleum, BP and Targa. The combined offering will integrate Zeitview's global inspection operations and AI platform with Insight M's methane detection capabilities. Zeitview operates in over 80 countries and has inspected more than 200,000 assets across telecom, wind, solar, property and utility sectors.

Zeitview acquires Insight M to bring roi-driven methane detection and asset intelligence to oil & gas operators. Insight M's methane detection expertise combined with Zeitview's predictive asset health strengthens an end-to-end critical infrastructure offering for the AI era Los Angeles, CA - February 11, 2026 - Zeitview, the leader in AI-driven asset intelligence for critical infrastructure, today announced that it has acquired Insight M, a leading methane detection and analytics company trusted by the largest oil and gas operators in the world. Uniquely, Zeitview now serves all key sources of energy generation (wind, solar, oil, gas), distribution, and consumption (commercial/industrial facilities, data centers). The acquisition marks Zeitview's entry into the oil and gas sector and significantly expands the company's ability to help operators maximize the return, reliability, and predictability of diverse energy assets, while supporting efforts to reduce emissions. Industry data shows that most methane emissions come from a small percentage of assets, where a few large leaks drive disproportionate product loss, operational risk, and regulatory exposure. Historically, operators lacked scalable tools to reliably identify these high-impact events, relying on legacy labor-intensive manual leak detection that couldn't keep pace with the scale of modern energy systems.