AI Agents
Agents that act inside a written boundary.
For established teams with recurring requests, known source records, and named reviewers.
We build bounded agents that interpret defined requests, use approved tools, route exceptions, and leave a reviewable trail. Each action is tied to explicit sources, permissions, and escalation rules.
Inside the system
The boundary is part of the product, covering sources, allowed actions, review points, and exception handling.
Inspect agent context
Approved response guidance selected. The draft and review boundary now reflect that source.
Representative support flow — drafted replies pass source checks and defined escalation before a customer-facing action.
Illustrative example — not a customer transcript or reported outcome.
Example systems
What the operating model can become.
Example system
Customer intelligence system
Turn calls, support conversations, and reviews into source-linked language patterns, objections, and messaging priorities.
- Operating boundary
- Analysis stays traceable to approved source material, and a named reviewer approves recommendations before they become public copy or operating policy.
Example system
Signal-led revenue workflow
Watch approved market signals, enrich matching accounts, and prepare contextual next steps for review.
- Operating boundary
- A signal is evidence for review, not proof that an account is ready to buy; suppression, deduplication, qualification, and approval rules are defined before any outreach action.
Delivery path
The workflow stays visible from request to handoff.
Inspect agent boundary
Authority selected. Approved sources define the answer space. Write access remains unavailable.
Representative agent control flow — source checks, decision boundaries, review, and an allowed action are shown without customer data.
Illustrative example — not a customer transcript or reported outcome.
Start with one bounded problem