Coram AI, a San Francisco-based startup, has secured $35 million in Series B funding to scale its autonomous security camera software, bringing its total venture capital raised to $66 million. The company uses AI agents to convert existing security infrastructure into searchable, automated systems, aiming to reduce the manual labor typically required for security monitoring.
How Coram AI’s Technology Functions
The platform, marketed as "Deep Investigation," functions as an AI agent capable of processing natural language queries. According to the company, users can search through months of video, entry logs, and visitor data across multiple sites to generate automated incident reports. The software operates on local NVIDIA hardware at the "edge," which the company claims allows it to process video feeds without transmitting sensitive data to the cloud.
The system integrates with existing IP cameras, allowing facility managers to add capabilities such as license-plate reading, tailgating detection, and real-time weapon detection without replacing physical hardware.
Who Is Backing the Expansion?
The Series B funding round was co-led by Ansa Capital and Battery Ventures. Additional participation included UP Partners, 8VC, and Mosaic Ventures.
The investment signals a broader trend of venture capital flowing toward companies attempting to build "operating systems" for physical spaces. As noted by Allan Jean-Baptiste of Ansa Capital, physical security represents one of the largest industrial sectors yet to undergo a comprehensive transformation by modern artificial intelligence. While traditional incumbents focus primarily on selling hardware and static dashboards, Coram AI is betting on a model where automated agents manage surveillance tasks autonomously.
Real-World Deployment and Scope
Founded in 2020 by Ashesh Jain and Peter Ondruska, Coram AI currently operates in more than 1,500 locations. The company’s client base spans diverse sectors, including schools, factories, and religious institutions. For example, a Dallas-based megachurch utilizes the platform to monitor 30,000 worshippers across eight separate campuses, while various high schools have adopted the system to facilitate real-time weapon detection.
The Trade-offs of Autonomous Surveillance
The shift toward autonomous security agents introduces significant questions regarding privacy and the ethics of constant monitoring. While the company emphasizes local processing as a privacy safeguard, the capability of these systems to draw their own conclusions across an entire network of cameras creates a new paradigm in surveillance.
Unlike traditional motion-detection systems that rely on human intervention, Coram’s agents are designed to function continuously in the background. As the company scales, the industry will determine whether the efficiency gains promised by these agents—such as the ability to resolve security incidents in minutes rather than hours—outweigh the concerns associated with deploying persistent AI oversight in public and private spaces.
Key Details at a Glance
| Feature | Description |
|---|---|
| Total Funding | $66 Million |
| Series B Lead Investors | Ansa Capital, Battery Ventures |
| Current Reach | 1,500+ locations |
| Core Technology | Local AI processing on NVIDIA edge chips |
| Primary Use Case | Natural language video search and incident reporting |
For now, the company’s performance metrics—such as claims of being "10x more effective"—remain internal projections. The coming years will serve as a testing ground for whether Coram AI can successfully transition its technology from a specialized security tool to a standard operating system for building management.