Prescient Security Launches Cait AI Pentester and Unifies Cacilian Platform

May 12, 2026
Prescient Security has launched Cait, a continuous AI-assisted penetration testing service, and integrated Cacilian as its unified PTaaS platform to support continuous, audit-ready security testing.

Prescient Security announced in a press release the launch of Cait, a continuous AI assisted penetration testing service, along with the integration of its Cacilian platform as the company’s unified penetration testing solution. The combined offering is designed to move organizations from single point tests to continuous, verifiable testing that aligns with frequent software releases and compliance requirements.

Cait, short for Cacilian AI, functions as an autonomous pentester that analyzes applications before conducting tests. It focuses on generating validated, audit-ready findings instead of raw scanner data. Delivered as a recurring AI assisted service, Cait enables teams to maintain ongoing test coverage without restarting consulting engagements after each code change.

Cacilian acts as the central platform for managing penetration testing activities. It supports structured intake, real time visibility, and integration of human-led assessments on top of Cait’s automated coverage. The unified system allows security and engineering teams to demonstrate continuous control effectiveness while reducing manual overhead.

According to Prescient Security, both Cait and Cacilian help organizations maintain continuous application and API testing with credible, exploit-validated results suitable for audits and compliance frameworks such as SOC 2 and ISO.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Cybersecurity AI Weekly or Daily AI Brief.

Also, consider following us on social media:

Free newsletter

Cybersecurity AI Weekly

Weekly newsletter about AI in Cybersecurity.

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more
Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.