Security evidence across the AI operating lifecycle
GhostFrame builds evidence-driven security systems for decisions that cannot rely on assumptions.
This integrated pilot gives security teams evidence across three moments: before operation, during an incident, and after contaminated AI knowledge has influenced behavior.
Qualify the agent before trust becomes access.
Evaluate an exact agent version against bounded behaviors, permissions, policy, and release conditions before higher-impact access is granted.
Know what they proved. Not what they claimed.
Turn incident assertions into a reviewable chain of evidence so responders can separate demonstrated facts from narrative confidence.
What did corrupted AI knowledge affect, and can we repair it?
In a controlled setting, investigate how contaminated knowledge may propagate into retrieval, decisions, and downstream behavior.
8–10 week integrated pilot
Select systems, claims, knowledge sources, and success criteria.
Run controlled qualification, incident, and contamination scenarios.
Review findings, evidence packages, limitations, and next decisions.
Payment structure