Most security cameras sit idle until after something goes wrong — recording footage that only gets reviewed once an incident has already occurred. Coram AI is betting that doesn't have to be the case.
The startup has raised a $35 million Series B, according to Business Insider, bringing its total funding to $66 million. Coram's pitch is straightforward: rather than ripping out the cameras organizations already own, it layers AI on top of existing security hardware to detect incidents as they unfold, not just document them afterward.
The approach sidesteps one of the biggest friction points in enterprise security upgrades — the cost and disruption of replacing physical infrastructure. By working with equipment already in place, Coram can sell its software to hospitals, warehouses, retailers, and other organizations that have already made large investments in cameras but get limited real-time value from them.
As reported by Business Insider's Rya Jetha, Coram's model shifts cameras from passive recorders into active detection systems, capable of flagging unusual activity as it happens.
The broader trend here matters: AI is moving rapidly into physical security, a market historically dominated by hardware vendors and after-the-fact forensics. If software layers can genuinely make legacy camera networks smarter, it lowers the barrier for widespread adoption — and raises new questions about surveillance, privacy, and who decides what counts as an "incident" worth flagging.