JLINC Your Data
Enterprise GRC was built around people, applications and processes that operate within relatively predictable boundaries. Agentic AI changes that model. Agents can access data, invoke tools, collaborate with other agents and take actions autonomously — often crossing systems and organizational boundaries in the process.
GRC platforms are evolving to define policies, assess AI risk and document controls around these new environments. But there is still a critical gap between the policies governing what AI should do and independently verifiable evidence of what AI actually did. Application logs and agent observability can describe activity, but ultimately the system being governed is still reporting on itself.
JLINC closes that gap. Verifiable Contractual Agreements establish the authority, permissions and policies governing an AI relationship, while JLINC's cryptographic signing creates independent evidence of the activity that occurs under those terms. The result is a trust and evidence layer that connects and tracks AI workflow from poilcy to authority to activity and finally proof. and gives enterprises — and their GRC platforms — a verifiable record of agentic AI in action.
Agents access data, call tools, interact with other agents and take actions autonomously. Traditional GRC platforms can define policies and document controls — but often depend on the systems being governed to report what actually happened.
JLINC closes that gap with cryptographically verifiable evidence of AI relationships and activity.
A VCA establishes the terms governing a relationship between endpoints— including identity, delegated authority, permissions, policies and obligations. As activity occurs, JLINC creates signed evidence of the resulting interactions.
Thanks to JLINC, GRC vendors now have a record of what was agreed, what was permitted and then what actually happened
JLINC can provide evidence of agent identity, delegated authority, policy and permission, data provenance, chain of control and AI activity. The evidence can be independently validated by governance teams, auditors, regulators and authorized partners.
Your customers are already asking how they will govern AI agents as those agents gain access to enterprise data, interact with other systems and begin taking actions autonomously. For GRC vendors, this creates an opportunity to extend the governance platform customers already trust into an entirely new category of enterprise activity.
JLINC provides the trust and evidence infrastructure underneath that experience. By integrating JLINC, a GRC platform can incorporate cryptographically verifiable evidence of agent identity, delegated authority, permissions, data provenance and activity directly into its existing governance workflows and dashboards. Your platform remains the placewhere the customer manages governance. JLINC provides the evidence layer thatmakes agentic AI activity verifiable.
That creates a faster path to market than building a new agentic trust infrastructure internally. JLINC can be embedded through APIs at the points where agents, data and systems interact, while the GRC vendor determines how that evidence is presented, incorporated into controls, connected to risk frameworks and used within the customer experience.
The partnership also creates a natural joint go-to-market opportunity. JLINC can bring GRC partners into enterprise AI opportunities where customers need a governance platform around the evidence we generate, while GRC vendors can bring JLINC into existing accounts that are beginning to deploy agentic AI. Together, we can offer customers a more complete solution spanning policy, control, verifiable activity and audit evidence.
As agentic AI moves from experimentation into production, enterprises will need their existing governance infrastructure to evolve with it. JLINC gives GRC vendors a way to make verifiable AI governance a native part of their platform— without having to build the underlying cryptographic trust infrastructure themselves.
Extend your GRC platform into agentic AI governance.
