Xygeni

Security teams don't have a detection problem anymore, most tools find plenty. What they lack is judgment: knowing which of a thousand findings is actually dangerous, and what to do about it. Xygeni is an AppSec platform built to answer that question with AI at every layer, not as a chatbot bolted onto a dashboard, but woven into how findings get found, understood, and fixed. Native scanners cover SAST, DAST, SCA, Secrets, CI/CD, and IaC. AI Triage evaluates every finding for real exploitability, reachability, and business impact, instead of treating every alert as equally urgent. Crucially, that intelligence isn't limited to Xygeni's own scanners: its ASPM layer ingests findings from third-party tools already in your stack and applies the same AI prioritization to them, so adopting Xygeni doesn't mean replacing what already works. Fixing is AI-driven too. Validated pull requests handle vulnerable code with one click, and trusted remediation flows manage dependency upgrades automatically, cutting manual triage and remediation effort dramatically. DevAI brings this into the IDE as a proactive agent that reviews code, including AI-generated code, as it's written, no prompting required. Xygeni also secures the AI your teams are building with. It continuously discovers AI assets across repositories, models, agents, MCP servers, skill files, prompts, and analyzes configuration files as security artifacts, catching unsafe entries conventional scanners read as harmless text. An AI-BOM exports on demand for auditors and regulators. Malware Early Warning uses ML-assisted detection to catch malicious open-source packages before a signature exists, closing the window most supply chain attacks exploit. One platform, one prioritization model, AI applied everywhere risk actually lives.