Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Today, we’re excited to share that key members of the team at Ensemble AI are joining Cloudflare to help accelerate our work in AI infrastructure and make it easier for developers to run powerful AI models efficiently at scale. Ensemble AI, founded in 2023 in San Francisco, has spent the last few years focused on one of the most important challenges in AI: making large models faster, smaller, and more cost-effective to serve, without sacrificing quality.

Security Insights provides actionable security recommendations for every Cloudflare account. To find these insights, we perform regular scans for all accounts, zones, and DNS records, looking for potential security risks and misconfigurations. However, two key issues emerged. First, our scans were too infrequent. Scans were only being performed every week or two, and therefore newly introduced security risks could remain undetected for up to two weeks.

For most of the Internet’s history, public and private infrastructure operated as separate worlds. Public applications lived behind content delivery networks (CDNs) and web application firewalls (WAFs). Private applications lived behind virtual private networks (VPNs), firewalls, and separate operational stacks. We think that distinction is becoming obsolete.

A few weeks ago, we wrote about Project Glasswing and what we observed when we pointed cyber frontier models at our own code. Since then, we’ve seen that the part of the post that has resonated most deeply is the argument that the architecture around the vulnerability matters more than the speed of the patch.

Cloudflare’s Threat Events provides security analysts with a window into the global threat landscape. The platform offers a peek into the immense traffic that Cloudflare processes every day, so you can see in real time which IPs are attacking specific industries or which threat actors are trending globally. However, translating that visibility into active mitigation has often been a manual, reactive process.

There isn't a CIO on the planet not worried about AI spend right now. CFOs are increasingly nervous, too. For fear of falling behind, many companies have pushed their employees to use AI as aggressively as possible. The edict was clear: "Move fast, we'll figure out the bill later." And for the most part, it worked: AI has been genuinely transformational for the teams that leaned in. But the costs are real: we’ve heard countless horror stories of huge bills and painful overages on token spend.