# New security, privacy, and product policy updates for Synthesia 3.0 Written by **[Alexandru Voica](https://www.synthesia.io/blog/authors/alexandru-voica)** April 1, 2026 Create AI videos with 240+ avatars in 160+ languages. In this article 1. [A new milestone in enterprise AI assurance](https://www.synthesia.io/post/new-security-privacy-and-product-policy-updates-for-synthesia-3-0#a-new-milestone-in-enterprise-ai-assurance) 2. [What we’ve changed since the start of the year](https://www.synthesia.io/post/new-security-privacy-and-product-policy-updates-for-synthesia-3-0#what-weve-changed-since-the-start-of-the-year) 3. [Building the security layer that makes AI adoption faster](https://www.synthesia.io/post/new-security-privacy-and-product-policy-updates-for-synthesia-3-0#building-the-security-layer-that-makes-ai-adoption-faster) --- ## **A new milestone in enterprise AI assurance** Synthesia is now certified for ISO 27701, alongside [ISO 42001](https://www.a-lign.com/resources/case-study-synthesia) and [ISO 27001](https://www.synthesia.io/post/synthesia-is-iso-27001-certified). In combination, these standards are a strong signal of enterprise-grade maturity across the full stack of trust: ISO 27001 validates an information security management system; ISO 27701 extends that foundation into privacy and the management of personally identifiable information; and ISO 42001 focuses on AI management systems: how AI is governed, monitored, and improved over time. Together, they create a coherent assurance story for organizations adopting AI video at scale: security and privacy aren’t treated as add-ons, and AI-specific governance is formalized rather than improvised. We also continue to monitor the development of emerging standards and governance frameworks that support safe and responsible AI development and deployment, and we aim to lead by example (as we did by becoming the first generative AI company to achieve ISO 42001 certification), setting the bar for enterprise-ready AI governance. We are also aware that although certification formalizes our management systems, responsible AI also requires continuous product iteration, red teaming, and enforcement refinement. ## **What we’ve changed since the start of the year** We’ve spent the last year refining the performance of our moderation systems and using appeals outcomes and red teaming insights to improve enforcement quality while minimizing disruption to legitimate enterprise use. These changes are enabled by better technology becoming available and by us investing more resources to improve the accuracy of our systems and the effectiveness of our teams. One place this shows up immediately is content moderation, our first line of defense. When we first implemented automated safeguards a few years ago, we intentionally tuned them to be strict. AI video was still an emerging capability, the threat landscape was volatile, and we chose caution over convenience. Over time, that approach has created friction for some benign use cases: false positives where the intent and context were legitimate, but the system still over-enforced. Our direction now is to preserve early detection while reducing unnecessary disruption, and we’re working with third-party vendors to further improve the accuracy of our moderation systems and reduce false positives. We’ve also evolved how we think about Avatars, because the category itself is evolving. Synthesia now supports two types of Avatars: 1. [Stock Avatars](https://help.synthesia.io/en/articles/6341418-what-are-synthesia-stock-avatars) based on paid actors or generated by Synthesia with AI. Stock Avatars follow [a dedicated set of policies](https://help.synthesia.io/en/articles/6341934-guide-to-content-moderation) that are typically more restrictive in order to protect the likeness of the actors we work with. 2. [Custom Avatars](https://www.synthesia.io/post/synthesia-new-avatars-dont-just-talk-they-take-action) based on the likeness of specific users who are real people or based on an AI-generated likeness that the user designs. Custom Avatars are governed by a more relaxed set of rules as they are based on the likeness created by a specific user. We have completed dedicated red teaming work to limit the creation of harmful content while still giving businesses the flexibility to design Avatars that fit their needs. More broadly, our position is simple: while creative choice expands, our moderation standards remain consistent across Avatar types, and we continue to prohibit the creation of Avatars depicting celebrities, public figures, or deceased individuals. Customizable Avatars are also a meaningful shift in how safety is implemented in practice throughout our platform. Unlike Avatars which are created from a real individual under explicit consent, AI-generated likenesses rely on an image model, an approach that expands creative flexibility but also changes where certain safeguards live. Because this creation flow relies on third-party AI models, we’re leaning more than we historically have on those providers’ own content moderation and abuse-prevention systems as an upstream layer of protection. Finally, we’ve made a change that’s less visible from the outside, but matters a lot to the day-to-day product experience: what happens when content fails moderation. Until recently, if a video was caught by our systems, the user could lose access to the entire video and its previous versions. Rejected videos now remain editable and can be resubmitted rather than being treated as deleted. When a video fails moderation, users can update the content and resubmit directly instead of starting over, and they retain access to prior versions that didn’t violate policy. ## **Building the security layer that makes AI adoption faster** AI video is becoming part of the infrastructure of modern work. The organizations adopting it aren’t looking for novelty, they’re looking for reliability, governance, and speed without surprises. That’s why we invest in proactive safeguards at creation time, layered enforcement that combines automated systems with expert human oversight, and external validation that stands up to enterprise scrutiny. We’ll keep strengthening the platform in ways that make responsible use the default and misuse harder over time, while continuing to treat enterprise-grade security, privacy, and trust as product features that accelerate enterprise adoption globally, responsibly, and at scale. ---