Give personal AI agents a secure way to identify who they represent, request what they need, and work with ALi on your terms.
Customer-owned AI agents send requests to ALi, where identity, permissions, policy and approved actions are evaluated before work reaches enterprise systems.
Illustrative personal-agent ecosystem. Product names belong to their respective owners. Example logos are shown for context only. No affiliation or endorsement is implied.
Customers are beginning to delegate research, comparison, booking, cancellation and service tasks to AI agents. Your business needs a way to accept those requests without giving up identity, permission or policy control.
Every incoming agent request should pass through one governed path before it reaches your systems or changes a customer outcome.
Identify whether the request comes from a person, personal agent or enterprise agent
Establish who the agent represents and the available identity context
Evaluate requested scope, customer permission and business policy
Expose only the workflows and systems approved for the request
Complete, request authorization, ask the customer or escalate
An agent request needs more than intent. ALi keeps the represented customer, requested capability, available authorization and business policy visible before approved actions are exposed.
Agents can exchange requests without allowing the interaction to drift forever. Policy boundaries, prior attempts and defined escalation paths keep the conversation moving toward a real outcome.
The request is completed within approved scope.
The customer is asked to approve an action beyond current scope.
A direct question returns control to the person, not the agent.
The interaction escalates to a person on your team.
Open agent protocols are creating a common way for independent agents to discover capabilities and exchange messages. MCP, APIs and workflows connect ALi to the systems that complete the work, while identity, policy and action remain separate control layers.
The value of agent-to-agent interaction is not another conversation. It is getting approved work completed with the right context, permissions and controls.
Move my trip to an earlier flight
What was my last payment?
Add international roaming for next week
Every request, permission decision, policy evaluation, system action and escalation should remain visible to the teams responsible for the customer experience.
Explore ConsoleNew personal agents, protocols, permission models and interaction patterns will keep emerging. Augmented Labs manages the operating layer around your agents, from testing and policy configuration to quality, analytics and continuous improvement.
Give personal AI agents a secure way to do business with yours.
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