TestSavant.AI · Checkpoint Technologies

AI Red Teaming

TestSavant Red-Teaming orchestrates datasets, synthetic adversaries, scheduled runs, and telemetry so teams can discover jailbreaks, data leaks, and brittle filters before customers or attackers do.

View AI Red Teaming on TestSavant.AI

How Checkpoint Technologies approaches this platform

Red teaming only creates value when findings tie back to release decisions and remediation owners. Checkpoint Technologies helps teams register model inventory, build datasets aligned to their application surface, configure repeatable playbooks, and interpret category scores so product and security stakeholders know what to fix before go-live.

What teams usually struggle with

AI testing is ad hoc prompt hacking with no repeatable cadence
Security and QA teams lack a shared evidence trail for AI risk
Model inventory and evaluation settings are unclear or incomplete
Findings do not roll up to release readiness or audit requirements
Teams cannot compare results across releases or policy changes

How Checkpoint Technologies helps

Assess AI surfaces, use cases, and risk priorities before platform rollout
Configure TestSavant model inventory and red-team settings for your stack
Design datasets using curated catalogs, Meta-Prompter, or internal CSV uploads
Set scheduled runs that match your release cadence and governance model
Train QA, product, and security teams on interpreting results and remediation
Support high-stakes releases with senior AI assurance expertise

Typical engagements

AI red-team readiness assessmentPlatform implementation and model inventory setupDataset and playbook designScheduled run operationsQA and product team training