Your Partner in AI Containment
Contain the risk. Protect the advantage.
AI is already inside the enterprise.
Employees are using it to summarize documents, draft client work, review contracts, analyze data, write code, prepare reports, and accelerate decisions. In many organizations, that adoption is happening faster than policy, security, legal, procurement, and governance teams can control.
The issue is no longer whether companies will use AI. They already are.
The harder question is whether leadership knows where AI is being used, what information is being exposed, which tools are approved, how outputs are being verified, and whether proprietary data remains protected by defensible controls.
Blacksite AI helps organizations identify, assess, and contain AI risk before it becomes a legal, cyber, reputational, or valuation problem.
Our work focuses on four connected areas:
- AI Containment Assessment
- Data Provenance Diligence
- AI Output Reliability Review
- AI Vendor Governance Review
Each solution is remote, structured, evidence-driven, and built to produce executive-ready findings with practical remediation steps.
WHAT WE DO
Blacksite AI turns AI uncertainty into operational risk intelligence.
Our assessments help organizations answer the questions that matter:
Where is AI being used?
Which tools are approved, restricted, prohibited, or unknown?
What sensitive information may be exposed?
Are employees using personal AI accounts for work?
Are trade secrets and proprietary data protected by reasonable controls?
Are AI-generated outputs being checked before they influence decisions or client work?
Are vendors retaining, training on, or exposing company data?
Are AI data claims and proprietary data moats defensible?
What should leadership fix first?
Blacksite AI assessments do not rely on surveys alone. We correlate available evidence across leadership intake, employee-use patterns, workflow analysis, policies, vendor documentation, technical visibility indicators, and control maturity.
The result is a practical view of where AI risk is known, likely, technically observable, or currently invisible.
