A custom agent is one you build yourself, with a library such as the Claude Agent SDK, the OpenAI Agents SDK or LangGraph, or with a plain script that calls a model in a loop. Developers use this route when no ready-made agent fits a job, or when the agent must run on a schedule, inside their own product, or on their own servers.
You get a structured P&L with each transaction classified, totals calculated with formulas, and a clear view of gross margin.
Each new lead gets a researched summary, a score, a route and a draft reply, and a person approves the action before anything changes in the CRM or reaches the lead.
You get a table of buyer questions with your mention rate, competitors' mention rates and cited sources per assistant, plus a short content plan for the biggest gaps that you approve.
You get a workbook with every bank line matched to a receipt or marked missing, a proposed category for each, and a short list of VAT or sales tax questions for your accountant.
You lower your bill, or get a firm answer from retention, without agreeing to a plan change or contract you did not approve.
You get a table of researched accounts with a fit score, sources and one draft email each, and nothing is sent until you approve it.
Each weekday you get one message with the few new papers and releases that match your interests, each with a link, a one-line reason it matters, and a clear note when nothing new appeared.
Every new support email gets a label, a priority and a draft reply grounded in your docs, and a person sends each reply after reading it.
Every booking in the date range sits on your calendar once, at the right local time, with the confirmation number and address in the event.
Every week you get a short briefing of meaningful changes to competitors' pricing and product pages, each with the before text, the after text and a link to the saved snapshot.