Reality Defender democ­ra­tizes deepfake detection with public API launch

The democ­ra­ti­za­tion of artificial intel­li­gence has been a double-edged sword. While generative AI tools have unleashed unprece­dented creative and produc­tivity possi­bil­i­ties, they’ve also armed bad actors with sophis­ti­cated deception capa­bil­i­ties that were once the exclusive domain of state-sponsored actors and well-funded criminal orga­ni­za­tions. Today, anyone with a smartphone can create convincing deepfakes that can bypass traditional security measures, manipulate financial markets, or destroy reputations in minutes.

It’s against this backdrop that Reality Defender​’s latest announce­ment takes on profound signif­i­cance. The company, which has been quietly protecting Fortune 500 companies and government agencies from AI-powered deception, has launched a public developer API and SDK with a free tier offering 50 detections per month. This isn’t just another API launch — it’s a fundamental shift in how we approach digital security in the age of synthetic media. See Fast Company coverage of the news here.

What makes this partic­u­larly compelling is the timing. As deepfake technology becomes increas­ingly accessible and sophis­ti­cated, Reality Defender is essentially betting that the defense against digital deception needs to be just as ubiquitous as the tools that create it. By making enterprise-grade deepfake detection available to any developer with just two lines of code, they’re attempting to build what they call a ​“distributed defense network.”

I caught up with Ben Colman, co-founder and CEO of Reality Defender, to discuss what this API launch means for the broader fight against AI-powered deception and how democ­ra­tizing detection technology could reshape digital trust.

DCVC: What drove the decision to make your enterprise-grade detection technology publicly available?

Colman: We’ve been incredibly successful protecting large enterprises and government agencies, but every success story came with a nagging question: What about everyone else? The reality is that deepfakes don’t discrim­i­nate by company size or budget. A single sophis­ti­cated deepfake can devastate a startup just as easily as it can harm a Fortune 500 company.

We realized that protection can’t be reserved for those with enterprise budgets. When we see deepfakes being used to manipulate local elections, defraud small businesses, or spread disin­for­ma­tion on social platforms, it becomes clear that detection needs to be everywhere — embedded in every app, accessible to every developer, protecting every user.

The API launch represents our commitment to enabling trust in an AI-powered world. We’re not just offering a platform; we’re building the infra­struc­ture for a more trustworthy digital ecosystem.

DCVC: How significant is the threat that individual developers and smaller companies face from deepfakes?

Colman: The threat is already substantial and growing expo­nen­tially. What’s partic­u­larly concerning is that the barrier to entry for creating deepfakes continues to plummet while the sophis­ti­ca­tion increases. We’re seeing attacks that would have required significant technical expertise and resources just two years ago now being executed by individuals with minimal training.

For smaller companies, the impact can be existential. They don’t have the resources to recover from a sophis­ti­cated deepfake attack that damages their reputation or enables fraud. A startup building a trust-based platform, a content creator whose likeness is being used maliciously, or a financial services company dealing with synthetic identity fraud — these orga­ni­za­tions need the same level of protection as our enterprise clients.

The democ­ra­ti­za­tion of creation tools demands a democ­ra­ti­za­tion of detection capa­bil­i­ties. That’s why we made our API production-ready from day one with the same multi-model detection capa­bil­i­ties that protect our largest clients.

DCVC: What’s your vision for this ​“distributed defense network” you’re building?

Colman: Imagine a world where detecting deepfakes is as routine as filtering spam. Where every commu­ni­ca­tion platform, every content management system, every social app has deepfake detection built in by default. Every developer integrating our API becomes part of a global shield against AI deception.

This is about creating ubiquitous protection. Our API introduces context-aware detection that looks beyond just faces — our proprietary techniques analyze entire images holis­ti­cally, marrying multiple types of approaches to catch sophis­ti­cated deepfakes that other systems miss. This makes our detection useful not just for catching imper­son­ations, but many other types of deepfakes in the wild.

The network effect is crucial here. The more developers integrate detection capa­bil­i­ties, the more data points we have to improve our models, and the more resilient the entire ecosystem becomes against emerging threats.

DCVC: How do you see this impacting the broader AI safety landscape?

Colman: This API launch is a step toward making AI safety infra­struc­ture as fundamental as cyber­se­cu­rity infra­struc­ture. Just as we don’t question whether websites should have SSL certifi­cates or whether apps should have authen­ti­ca­tion, we shouldn’t question whether platforms should have deepfake detection.

We’re at an inflection point where the tools to impersonate are evolving daily. The tools to detect must be everywhere and then some. By making detection accessible to any developer, we’re not just protecting individual appli­ca­tions — we’re building the foundation for an AI ecosystem where trust can be verified, not just assumed.

The broader implication is that we’re moving from a world where deepfake detection is a luxury to one where it’s a necessity. Every developer building trust-critical appli­ca­tions — whether that’s a dating app, a financial platform, or a news aggregator — now has access to the same detection capa­bil­i­ties as the largest institutions.

DCVC: What’s next for Reality Defender and the API?

Colman: We’re expanding beyond audio and image detection to video and other modalities in the coming months. But more importantly, we’re focused on making integration even simpler and more powerful. We want to get to a point where adding deepfake detection to an application is as straight­for­ward as adding a payment processor.

We’re also working on industry-specific solutions that leverage the API foundation. Think specialized detection for financial services, media veri­fi­ca­tion for newsrooms, or identity veri­fi­ca­tion for hiring platforms. The API is the foundation, but the appli­ca­tions are limitless.

The ultimate goal is to make deepfake detection invisible to end users while being indis­pens­able to developers. We want to enable a world where digital inter­ac­tions can happen with confidence, where trust isn’t just assumed but verified in real-time.

This API launch is several giant steps forward toward making that reality. The tools to impersonate are evolving daily — now the tools to detect can be everywhere they’re needed.