Collaborate on applied AI security research and evidence.
The research program supports vulnerability discovery, benchmarks, adversarial datasets, disclosure workflows, and evidence-backed AI security reporting.
Research routes
Research collaboration should produce credible outputs without confusing research access with unrestricted commercial use.
Partners
OEM, scanner-provider, MSSP, reseller, consulting, private-label, and technology partner programs.
Licensing
Enterprise, embedded, OEM, white-label, offline, air-gapped, academic, startup, and usage-credit licensing.
Operations
Deployment, support, SLA, security, data-processing, audit, success, and implementation operations.
Commercial Contact
Start an OEM, reseller, MSSP, enterprise, private-label, procurement, or deployment conversation.
Turn field research into useful security evidence
The best research work should improve coverage, generate safe disclosures, strengthen benchmarks, and create usable evidence.
Measure real AI risk
Create repeatable tests for AI applications, RAG systems, and agents.
Support safe vulnerability work
Coordinate findings, public-safe reporting, and remediation evidence.
Build adversarial corpora
Improve scanner modules with grounded examples and realistic fixtures.
Build the right commercial path
Use a focused pilot to align the technical integration, licensing structure, support model, and customer-facing packaging.