How we build an agent that’s yours.
A branded AI agent isn’t a plug-in. It’s a new teammate — onboarded the same way you’d onboard a great hire.
Define outcomes
We start by agreeing on what “done” looks like for every mission. Not “conversations resolved” — specific, verifiable outcomes: COI delivered, policy bound, endorsement processed, quote comparison complete.
- Missions chosen and scoped
- Success criteria in your language
- Escalation criteria and handoff context
Set guardrails
Every action the agent can take — and every one it can’t — is defined up front. Carrier-specific rules, payment thresholds, binding authority, state compliance, data boundaries. The agent only acts inside the box you draw.
- Bind authority and thresholds per mission
- Human-in-the-loop triggers
- Compliance boundaries and audit requirements
Capture SOPs
We sit with your top producers and account managers and capture the real SOPs — how you actually issue a COI, how you handle a pending cancellation for non-payment, how you prep a renewal. Turned into an executable runbook the agent follows.
- Interview producers and AMs doing the work
- Pull past examples as ground truth
- Encode SOPs as agent-executable workflows
Connect the stack
An agent can only act if it has real access to the systems where the work happens. We wire into your AMS, CRM, carrier portals, inboxes, and payment rails — with auth, scoped permissions, and a full audit trail from day one.
- AMS read/write — AMS360, Applied Epic, HawkSoft, QQ Catalyst, AgencyZoom
- CRM (Salesforce, HubSpot), inbox (Outlook, Gmail), collaboration (Slack, Teams)
- Carrier portals per appointed market
- Scoped permissions; every call logged
Simulate & test
Before a single real insured talks to the agent, it runs against a battery of simulations built from your past conversations and the edge cases your team sees in the wild. Regression tests catch drift before it hits production.
- Simulation runs against historical tickets
- Edge cases captured as permanent tests
- Side-by-side reviews with your team before launch
Deploy & improve continuously
Rollout is gradual — shadow, then supervised, then autonomous on approved missions. Every conversation and every tool call is observable. Over time the agent gets sharper as new edge cases become tests and new missions come online.
- Shadow → supervised → autonomous per mission
- Every action logged, searchable, auditable
- Ongoing reviews turn escalations into tests
Ready to start?
Tell us about the moments you’d most like an AI agent to carry. We’ll come back with a scoped plan and a realistic timeline.