Custom AI agent development means the agent is designed around your process, not the other way round. We write the scope with you, quote it in writing before any work starts, and connect the agent to accounts you already own. It does the legwork, your people approve what matters, and the result is your own Jarvis.
A generic agent assumes a generic business. Yours has its own approval steps, its own spreadsheet nobody dares rename and its own exceptions. The agent ends up half-used because it was never shaped to any of that.
A zap fails when a field changes, and nothing tells anyone. Weeks later a lead has gone cold or an invoice was never chased. Nobody owns the automation, so nobody notices it stopped.
A proof of concept impresses in a meeting, then waits for budget, a second phase and a handover that never comes. Meanwhile the real work still lands on your team every morning.
| When | The assistant | You or your team | Result |
|---|---|---|---|
| A new inbound lead arrives through the website form or a shared sales inbox | Looks up the company and the person, scores the lead against your qualification rules, writes a short research note into the CRM and drafts a reply for the sales owner | The sales owner edits and sends the reply, or marks the lead as not a fit | Every lead has a researched note and a draft waiting in the CRM within minutes of arriving |
| An invoice passes its due date in the accounting tool | Sends a staged reminder sequence by email: a friendly nudge on day 1, a firmer one on day 7 and an internal flag on day 14, each drafted from the invoice record | The account owner approves each external reminder, and the finance lead decides on any escalation | Overdue invoices move through a visible ladder in the tracker instead of waiting for someone to remember |
| Every Monday at 7:00 AM | Pulls last week from the ad platforms, analytics and the sales sheet, builds the weekly metrics report in your template and flags anything that moved more than the threshold you set | The owner reads the report and replies to the flagged items with a decision | A finished weekly report is in your inbox and the shared folder before the first meeting |
| A client signs the proposal in your e-signature tool | Creates the project in your task tool from your onboarding template, requests logins and files from the client, and chases any missing item every two days | The account manager approves the first outbound message and confirms access is complete | Onboarding starts the same day, with a checklist anyone on the team can open and read |
| A support email lands in the shared help inbox | Reads it, tags it as billing, bug, request or complaint, pulls the customer record and drafts a response using your approved answers | A support teammate reviews the draft and sends it; complaints route to the owner | The inbox is sorted by category with a draft attached to each routine message |
The agent finishes its overnight run: new leads researched, support mail sorted, overdue invoices listed. A short summary arrives in Slack.
Your sales owner opens the CRM and finds three qualified leads with notes and reply drafts. They edit one line and send.
A client signs a proposal. The project, the checklist and the first access request appear without anyone typing them.
The agent asks for approval on a day-7 invoice reminder. The account owner reads it, changes the tone and approves.
A support email arrives in a category the agent has not seen before. It drafts a reply, marks its confidence as low and routes it to a person.
You review the run log: what the agent did, what it asked about and what people changed. You tune one rule and ask for a new workflow next.
If a tool has an API or an export, it can usually be connected.
You receive a written scope and quote before we build anything. If the work grows, it becomes a new, separately agreed scope, never a surprise on an invoice.
You can see what the agent read, what it decided and what it asked a person about. When something looks odd, you read the log instead of guessing.
If a connection drops or a step cannot finish, the agent reports it to a named person. A broken workflow shows up as a message the same day.
The assistant drafts. A person on your team sends.
This isn't a template with your logo on it. Every build starts from how your business actually runs — so there's no off-the-shelf demo, and we won't pretend otherwise.
We map how your week and your business actually run, and pick the first tasks worth handing over.
On the strategy call we build one of your real tasks with AI, on screen — your data, not a generic demo.
We scope the build with you on a strategy session and quote it in writing — agreed before a single workflow is built.
The assistant is wired into your tools, with inputs set up for each person on your team.
We go live, then tune reminders, reports and sign-offs as your team settles in.
An AI agent is software that reads information, decides the next step and acts through your tools, inside rules you set. A chatbot only answers questions, and a plain automation follows fixed steps. An agent handles the messy middle, such as reading an email and choosing what happens next.
Build custom when your process has its own steps, approvals and exceptions that a platform template cannot express. Platforms suit common, simple jobs well. A custom agent costs more upfront but fits your tools and rules exactly, and you own it rather than renting a feature set.
We choose the model for each task rather than committing to one vendor. A model like Claude may suit long documents and careful drafting, while GPT or a smaller model may suit quick classification. If a better option appears later, the agent can be moved to it without a rebuild.
We stay on for a tuning period after launch, adjusting rules, reminders and wording as your team settles in. After that you can keep us on for changes or run it yourselves. It lives on your accounts, with documentation, so you are never locked in.
Every agent is quoted on a strategy session, after we understand the process it has to run. The quote depends on the tools, workflows and people it covers, and it is written down before work starts. We cover AI usage during the build; after handover it runs on your accounts, with optional monthly or yearly maintenance.
A single workflow can be live in about 7 days. Larger builds with several workflows and tools are delivered in phases, so the first agent is working while the next one is built. We give you a timeline in the written scope, before you commit.