01 / Security
Security agent builders
Design an environment around the systems, signals and response choices your agent needs to handle.
Scope your environmentThe product
Build the world your agent needs.
Synthetic environments, scenarios and feedback for teams building and deploying AI agents.
Start with the task, interfaces and system your agent operates in — from security and pricing to business workflows. Shape the environment and improvement process around them.
Discuss your environment01 / Built around your agent
Different agents.
Different worlds.
Start with the task and operating context. Build the environment, scenarios and feedback around the agent.
02 / Pricing
Pricing system deployers
Explore pricing policies, market interactions and operating constraints in synthetic markets.
Explore pricing research03 / Workflows
Business-workflow builders
Recreate applications, records and rules for agents that carry out work through browsers and tools.
See recorded workflowsExplore current work
Browser workflows in practice.
Two recorded environments show how agents work through applications, shared state and operating rules.
01
Payments
Recorded workflow
Apply a payment correctly.
Read the remittance, check the invoice and balance, obtain approval, post the allocation and verify the result.
02
Service desk
Recorded workflow
Coordinate a temporary laptop.
Check the request and inventory, agree the allocation, obtain approval and reconcile the reservation across two agent roles.
Both workspaces use synthetic business data. The service-desk recording ends with a reservation and scheduled pickup; physical handoff remains pending.
03 / The infrastructure
Build the world.
Train for the work.
Bring together the environment, scenarios, evaluations and feedback your agent needs. Work with us from environment design through targeted improvement.
Build the world
Map the task, system state, permissions and exceptions. Create the environment and a useful range of tasks.
Environment + scenario set
Run the agent
Connect the agent to the agreed browser or tool interfaces. Capture actions, intermediate state and final outcomes.
Runs + inspectable traces
Evaluate the work
Design outcome checks and feedback. Identify failures, rule violations and cases that need broader coverage.
Evaluators + failure analysis
Improve and retest
Choose prompt, workflow or reinforcement-learning updates to fit the agent. Rerun evaluations and check regressions.
Targeted updates + retest plan
Runs you can inspect
Start with the recorded work.
The current demonstrations show payments and service-desk agents using real browser interfaces with synthetic business data. The laptop workflow ends with a reservation and scheduled pickup.
Training and retesting are tailored to the agent and task. The historical API experiment has its own measured result and scope.