AI Security and Safety for Enterprise Usage

Generative AI has moved from pilot to production faster than any technology before it — and faster than the security tooling built to contain it. Models now read customer records, draft regulated communications, and take actions inside core systems. The attack surface they create is unlike anything in a traditional security programme: prompt injection, jailbreaks, data exfiltration through completions, and training-data poisoning that leaves no trace in a code review.

Vulcan, built by AIFT, is an AI security platform that covers the full lifecycle of a GenAI system.

Vulcan Attack red-teams models and LLM apps before they ship. It runs AI-driven adversarial campaigns against your own app, in your own deployment, surfacing the jailbreaks, leakage paths and robustness failures that generic benchmarks miss — and compressing a risk assessment that would take a specialist team 200 hours into roughly three, fully automated.

Vulcan Protect takes over once the system is live. Delivered as a single HTTP guardrail API rather than an SDK or sidecar, it inspects both sides of every exchange — input and output — and returns a safe/unsafe verdict with a per-category breakdown, plus sanitised content and PII-masked content ready to pass downstream. It handles text and binary payloads, covering DLP, security, compliance and content moderation in one call.

Behind the platform is an offensive team that runs more than 500 penetration tests a year, found over 1,000 vulnerabilities in 2024, and placed first at HITCON Cyber Range 2024. Where a platform isn't the right starting point, the same team delivers expert-led AI red teaming, classical penetration testing, and C-level AI security consulting and training.