How Traceable AI Works
platform
A modern foundation for cloud-native app security
with agentless and in-app data collection
Traceable AI collects API traffic across your entire application landscape and uses its advanced context-based behavioral analytics AI engine to show you all your APIs and what data they expose, block known and unknown attacks, and provide threat analytics and forensics.
Traceable AI fits into your existing infrastructure quickly and without friction, with its agentless deployment options, including out-of-band traffic mirroring. Traceable AI also provides language agents for those who need to be closer to the code for enhanced API call level troubleshooting and analytics. For efficiency and compliance, Traceable AI can keep all data inside a customer’s networks, or scrub it of sensitive data before sending transaction meta-data to the Traceable AI cloud.

distributed tracing
You can’t secure what you can’t see.
Traceable AI’s distributed tracing collects user activity, API activity, data flow, and code execution data, from all levels of your stack to enable complete security observability across your entire application landscape.

Why distributed tracing?
Distributed tracing is an observability technique where lightweight agent modules collect code-level diagnostic data from within production applications as code executes. Combined with mirrored network traffic, it spans multiple microservices and is an extremely powerful yet low overhead method to collect runtime application data related to application security. This technique greatly increases the accuracy and depth of threat detection and protection.
Why make it open source?
We’ve made our distributed tracing technology open source through the HyperTrace project because we believe everyone deserves complete observability into their applications.
Testimonials
intelligence & learning
Continuous full
application context.
The Traceable AI platform continuously learns from the distributed data collected to build a baseline of what normal API and app behavior looks like across your cloud-native apps. Then it compares each activity against this baseline, automatically detecting when behavior deviates from the norm.

Why machine learning?
Only machine learning can keep up with the evolving threats of modern attacks. Traceable uses multiple machine learning techniques like deep learning, clustering, classification, unsupervised learning and more for a complete view of your APIs and cloud-native apps.
What powers the AI?
Machine learning is only as good as the data you feed into it. We use multiple forms of distributed tracing (out-of-band and inline options) to inform our AI so it’s always on guard to detect and block anomalous threats from API attacks, business logic attacks, and even unknown attacks.
Easy to get started
1. Sign up
Register using your Google login or your email address. Enterprise customers can also use well-known IAM providers such as Okta.
2. Configure Traceable AI to collect API traffic
Traceable AI guides you in configuring data collection (agentless or with in-app agents). Configuration is designed to be fast, easy, and low friction to get you securing your APIs quickly.
3. Discover, protect, and analyze
Congratulations! You have all the required configurations set up to experience the benefits of tracing and machine learning for securing your APIs.
Other resources
Keep up with
constant change.
Get the inside trace.
Application architectures and the security landscape is constantly changing. How do you keep up to date? What are the latest thoughts on protecting your applications?
(R)evolution in
Application Security
The application renaissance has begun. Delivering new application features and functions every two weeks is now table stakes. Learn how to re-think security for the future.
Personalized
Traceable Demo.
Want to see Traceable in action and learn how you can dramatically improve your application security posture in minutes?