November 6, 2024 4:00 PM
CET
How to improve the security, scalability and intelligence of your access control
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Run autonomous AI agents you can actually control
IndyKite AgentControl governs how AI agents retrieve data, use tools, and take action — context-aware, enforced in real time, and fully traceable.
- Give every agent the right permissions at the moment it acts
- Set guardrails once — enforce them on every action
- Trace every agent decision for full accountability
See AgentControl in action
Book a personalized demo with our team.
Trusted by leading enterprises
How does AgentControl work?
Autonomous agents act faster and at greater scale than people can supervise manually. AgentControl applies runtime control to every agent action, ensuring agents only retrieve data, use tools, and take actions that are appropriate in the current context. Every decision remains fully traceable, providing the control required to deploy autonomous AI with confidence.
Decisions at the moment of action
Control is enforced the instant an agent queries data, calls a tool, or triggers a workflow.
Context-aware by default
Every decision evaluates live signals including provenance, data sensitivity, relationships, and current context, ensuring agents only retrieve data and perform actions appropriate for the task.
One control layer, every agent
Set guardrails centrally and apply them consistently across in-house agents, third-party copilots, and machine-to-machine workflows.
Provable, not assumed
Every agent decision is recorded and fully traceable, so you can show exactly what an agent did, what it touched, and why.
Power contextual decisions at runtime
This context is evaluated at the moment of use to determine who or what can access which data, under what conditions, and why.
Context computed, enforced, and auditable in real time.
Apply live context directly to enterprise AI queries
Mobilize sensitive data safely across teams, partners, and AI systems
Prove compliance instantly, with full decision traceability
Build products and services that were impossible under static controls
Control agents in three steps
01
Connect your enterprise context
IndyKite builds a live knowledge graph of your identities, data, systems, and relationships, providing the context used to control every agent action.
02
Apply dynamic, granular controls
Configure context-aware controls that govern how AI systems retrieve data, use tools, and interact with enterprise services.
03
Enforce and trace in real time
Every agent action is evaluated and recorded at runtime, providing a complete, queryable history for security and compliance.
Hear from our customers
With IndyKite’s Platform, we will be able to support new and market-unique methods of onboarding and securing customers, inject more value for customer loyalty programs, drive new flexible payment and check-out solutions, and cross-brand benefits, ensuring our customers enjoy personalized, relevant, and rewarding experiences every time they engage.
Erik Torkildsen,
Head of Identity and Payments at Rema 1000
It’s helping PACCAR more quickly and reliably deliver value to our customers and make better decisions faster internally. We’re excited to be working with IndyKite.
Dallas Thornton,
Director Digital Services, Paccar
IndyKite’s platform offers the scalability, flexibility, and security needed to optimize our data management across our enterprise systems.
Ryan Carpenter,
Vice President, Commercial Programs & Operations at Rockwell Automation
IndyKite serving as an aggregator not only for Deutsche Telekom but for the entire CAMARA community and a broad range of services opens up possibilities for a range of clients that can benefit from accessing rich data they would not otherwise have access to - demonstrating the power of this initiative in action,
Peter Arbitter,
SVP MACE, a Deutsche Telekom initiative
AI agent security questions
How do you control AI agents in real time?
IndyKite AgentControl applies runtime control to every agent action. Using live context, agents are evaluated as they retrieve data, use tools, and interact with enterprise systems. Every decision is enforced in real time and fully traceable, providing the control required to deploy autonomous AI with confidence.
How do you secure autonomous AI agents?
IndyKite AgentControl evaluates every agent action against a live knowledge graph of enterprise context. Signals such as provenance, data sensitivity, relationships, and current conditions help determine how data is retrieved, how tools are used, and what actions are appropriate. Every decision remains fully traceable for security and compliance.
How do you govern AI agent actions?
IndyKite AgentControl applies dynamic, context-aware controls to every agent action. As agents retrieve data, use tools, and interact with enterprise systems, decisions are evaluated in real time and recorded for security, governance, and compliance.
How do you trace AI agent decisions for compliance?
With AgentControl, every agent actionl is recorded and fully traceable. Organizations can understand what an agent did, what data was involved, and the conditions under which decisions were made, helping support security investigations, compliance requirements, and audit processes.
How do you prevent AI agents from exceeding their permissions?
AgentControl evaluates every agent action against live enterprise context rather than relying on static permissions alone. Context such as data sensitivity, provenance, relationships, and current conditions helps ensure agents only perform actions appropriate for the task at hand.
How do you secure multi-agent workflows?
AgentControl applies runtime control to every step in a multi-agent workflow. As agents retrieve data, invoke tools, or delegate tasks to other agents, each action is evaluated against live enterprise context and recorded for full traceability. This allows organizations to deploy multi-agent systems with confidence while maintaining security, governance, and accountability across the entire workflow.
How do you get started with AI agent security?
Most organizations begin with a focused use case and a small number of agents. With AgentControl, IndyKite helps teams establish runtime control by connecting enterprise context, applying dynamic controls, and providing full traceability for agent actions. A focused demo can be tailored to your AI initiatives, systems, and governance requirements.
