A methodology from hands-on practitioners. It does not stop at a report.
Building the AI is often the easier part. Securing and governing AI systems is harder. Generic controls added late are easy to bypass, difficult to tune, and rarely reflect how the system actually behaves.
Most LLM systems share similar problems. And most security controls work in similar ways. We study both, so we know what works, when it works, and what does not.
Security comes from doing the right things in the right order. Understand the system, name the problems, fix what matters first, modify AI architecture, test and tune guardrails, define harness and boundaries, and build evals that reflect how your solution actually runs.
From the first call to a safer system.
Three stages, low friction, impact oriented, iterative.
Risk Audit and Engagement
We build prioritized action plan against your risk profile.
Measurable security
A safer system. You own the IP.
Common steps most organizations adopting AI need to perform.
Not a full list. In an engagement, actions and steps are chosen precisely for your system, your context, and your risk profile.
SafeDescent starts with a lightweight process to understand AI risk across your systems and use cases. Whether you are working from internal standards or external references such as the OWASP Top 10 for LLMs, NIST AI RMF 1.0, or the EU AI Act, we identify the risks that matter first and turn them into a practical set of steps.
You know your allowed use cases. You know how your users behave. That knowledge cannot live inside someone else’s black box. SafeDescent helps you trust, understand and improve your AI risk controls.
Evaluations should not be manual checklists or generic benchmark runs. SafeDescent turns what it learns about your domain, systems, policies, documents, and risk patterns into evaluation datasets, red teaming attack vectors, and behavioral checks your teams can run as part of regular AI operations.
AI systems operating with high autonomy need supervision beyond manual review. SafeDescent monitors agentic behavior, anomalous patterns, unverified outputs, and actions that exceed defined limits, giving human reviewers clearer signals and stronger control.
AI governance is more than policy storage and audit evidence. SafeDescent connects security, engineering, data, and regulatory perspectives into one strong operating picture, where assessments, safeguards, supervision, evaluations allow you to run AI systems with confidence and according to your rules.