What happens after launch?

You own the code, prompts, and logs, with documentation and a walkthrough. A care plan from $500/mo covers weekly log reviews, guardrail tuning, and new capabilities — or your team runs it and books us when the scope grows.

AI Agents That Act: CRM, Refunds, Invoices

Delivery blueprint

Visual summary of what this build includes from quote to handover.

Scope

Written

Deliverables and acceptance checks are fixed before build.

Execution

Instrumented

Retries, logs, and alerts are configured for production.

Controls

Approved

High-risk actions are gated by named human approvers.

Transfer

Owned

Runbook and account ownership move to your team at launch.

Your team is the integration layer

The queue never sleeps. Tickets, refund requests, overdue invoices, and CRM updates pile up overnight and across weekends, so every morning starts with digging out instead of moving forward. Across 2026 surveys, knowledge workers lose 6–7 hours a week to exactly this class of repetitive task.

Chatbots made it worse in one specific way: the AI tells the customer “your refund is on the way”, and a human still has to open Stripe, find the charge, issue the refund, update HubSpot, and close the ticket. Four systems, one copy-paste each, every single time. Each handoff is a delay and a chance to fat-finger an amount.

What we build

Queue-working agents

Claude-based agents connected to your helpdesk and inbox: they triage, resolve routine items end-to-end, and leave a draft for approval on anything ambiguous. The overnight queue is worked before your team logs in.

Claude · Zendesk · Gmail

Action layer with hard guardrails

Every action the agent can take is allowlisted with limits — refunds under $200 run themselves, anything above pings a human in Slack for one-tap approval. Every action lands in an audit log in Postgres.

Slack · Postgres · n8n

Integrations that do the writing

The agent updates HubSpot, issues Stripe refunds, and chases QuickBooks or Xero invoices through their real APIs — no browser puppeteering, no brittle screen-scraping.

HubSpot · Stripe · QuickBooks · Xero

How this ships

Week 1

Audit

Task inventory: which queue items an agent can own end-to-end, which need approval, and which stay human

Week 2

Blueprint

Agent spec: the tools it may call, action limits, approval rules, escalation paths, and the metrics that define done

Weeks 3-5

Build

Agent live on one queue in draft-for-approval mode, then acting autonomously inside its limits

FAQ

What does an AI agent build cost?

A single-queue agent with 1–2 integrations runs $2–6k; most builds — multiple systems, approval flows, monitoring — land in the $6–20k band. Fixed written quote after a free audit. Ongoing cost is model usage plus hosting, typically $40–180/mo.

How long until the agent is doing real work?

It works in draft-for-approval mode inside 30 days: the agent does the task, a human clicks approve. Once its approval rate holds above 95% for 2 weeks, we widen the limits and it runs those tasks itself.

Which systems can agents act in?

HubSpot, Salesforce, Zendesk, Stripe, QuickBooks, Xero, Gmail, Slack, and Google Sheets are standard; anything with an API is fair game. n8n handles the plumbing, so adding a system later doesn’t mean rebuilding the agent.

What stops the agent from doing something it shouldn’t?

Allowlisted actions with hard limits, human approval for anything outside them, a full audit log, and a kill switch that pauses the agent instantly. Data-wise: API calls run under commercial terms and aren’t used to train models, and credentials stay in your own infrastructure.

AI agents: the queue cleared by 9 am