Not a chatbot. A trained member of your team that reads the inbox, drafts the quote or the reply, works the hard requests, and checks its own work — any hour of the night. Your people review and release everything. Nothing goes out without a human.
Quotes, intake, and follow-up are won by whoever answers first — and lost in the 128 hours nobody is answering.
A quote request that lands Friday evening sits untouched for the whole weekend. By the time your team opens it, the customer has three other answers. In quoting, response time is close rate — and off-hours are where response time goes to die.
When the counter is slammed, new emails queue behind whoever is standing at the desk. The requests that wait longest are often the biggest ones — multi-line lists and engineered jobs that take real time to work up.
One veteran knows the catalog, the crosses, the sizing rules, and the gotchas. Every hard request routes through them — and when they're out sick, on vacation, or they retire, that knowledge walks out the door with them.
A mismatched part, a wrong substitution, a missed spec — each one means returns, freight, rework, and a customer who trusts you a little less. Speed without accuracy just delivers the mistake faster.
Trained on your catalog, your pricing rules, and your house policy. It does the work — your people keep the judgment calls and every send.
Free text, a parts list, a bare catalog number, a forwarded thread — it extracts what the customer actually needs and never guesses a value that wasn't stated. Missing information triggers a courteous clarification, not a wrong assumption.
Matched to your catalog, priced by your rules, formatted like your documents, with every assumption disclosed on the page. A draft is waiting for review about two minutes after the email lands — at 2pm or 2am.
When the easy answer doesn't exist — a cross-reference, a spec you don't stock, a ten-line request — it investigates: checks the catalog, verifies the details, and writes up exactly what the vendor call needs to ask. Your rep starts from a finished workup, not a blank screen.
"Make that two of them." "Same as last time." "Go ahead." It reads follow-ups in the context of the thread, updates the quote accordingly — and when a customer says yes, it recognizes a sale and hands it to your team. It never closes a deal on its own.
Before a human ever sees a draft, it is audited twice: the details are verified against what the customer wrote, and the math is recomputed independently. A draft that fails its own check is flagged and locked until a person clears it.
House rules live in plain English — "never quote X against Y," "always disclose Z." Write the rule once and every draft obeys it from the next email on. No retraining meetings, no compliance drift between people, branches, or shifts.
The reason this is safe to point at your customers: the AI drafts, deterministic rules verify, and a human releases. Three fences, in that order, every time.
Draft-only is structural, not a setting. Every quote and reply waits for a person to review and release it, and every release is logged — who, what, when, to whom.
Pricing, matching, and engineering run in deterministic code — plain rules, not AI guesses. The AI layers read, investigate, and review; everything they propose has to pass the hard gates before a customer could ever see it.
Each real email that ever exposed a gap is locked into a regression suite and replayed on every change. The system provably cannot repeat a mistake it has been corrected on. Ask any human employee for that guarantee.
Your business is open about 40 hours a week. Your inbox is open 168. An AI employee covers the other 128 — nights, weekends, holidays, and every minute your team is slammed — so the first thing your people do each morning is release finished work, not dig out of a backlog.
Our flagship AI employee runs a live quoting desk for wholesale pump & motor distribution — one of the most spec-heavy quoting jobs there is.
From a plain-English well description it solves the actual pump operating point, checks the motor against engineering rules, sizes the electrical package to code, and prints the full worksheet on the quote — so the reviewing rep sees every number behind the price.
Incompatible frame constructions, safety-class enclosures, lookalike substitutions — blocked by hard rules, with the reason stated in writing. When a ten-line cross list can't be filled from stock, it drafts the honest customer reply and the exact vendor request instead.
Catalog in, policy in, documents out. The same build pattern fits any email-driven desk with repeatable judgment work: distribution quoting, service intake, order status, dispatch triage, estimate follow-up. If your team answers email with expertise, an AI employee can draft it.
No integration project, no IT lift. It starts with the data you already have and proves itself before it touches a customer.
We study the desk we're staffing: a catalog or price export you already know how to run, plus a stack of recent real requests and what your team actually answered. That's the whole ask — nothing installed on your network.
The AI employee replays your past requests and we score its drafts against what your desk really quoted — together, line by line. You see the match rate on your own data before a single customer is ever involved.
It joins the inbox and drafts around the clock; your team reviews and releases. House rules get sharper every week — and every correction becomes permanent. Deeper automation is earned with a track record, never assumed.
No — it changes what their hours are worth. The AI employee does the transcription, matching, drafting, and first-pass investigation; your people review, decide, sell, and release. Every revenue moment and every send stays human. Most teams experience it as their best person getting a tireless junior, not as a replacement.
It drafts — it cannot send. Every draft is self-checked before a human sees it, a failed check locks the draft against release, and every correction becomes a permanent regression test that is replayed on every future change. When it errs, it errs toward holding a right answer for review, not toward releasing a wrong one.
Your catalog, quotes, and history live on infrastructure you control. Email text is processed through a commercial AI API under business terms — it is not used to train public models. Your cost and margin data is never even shown to the AI layers; they work with customer-facing numbers only.
Email-driven work with repeatable judgment: quoting desks, customer intake, order status and lead-time questions, estimate follow-up, dispatch triage, cross-reference research. If your team answers it by email using knowledge that lives in a catalog, a price file, or house rules, it's a candidate. The first build is scoped to one desk, done well.
A chatbot talks. An AI employee produces finished work product — a priced, formatted, self-checked draft document — and it's accountable: hard rules it cannot break, an audit trail for everything, and a test suite that proves its behavior on your real history. The conversation is the input; the work is the output.
No. The pilot needs an export you already know how to run (catalog, price file, or stock report) and a sample of recent real requests with your team's actual answers. Nothing is installed on your network, and deeper integration only happens after the pilot earns it.
30-minute free audit. We map your intake and quoting workload, show you which parts an AI employee can carry, and what a pilot on your real history looks like. No pitch. Keep the findings either way.
Claim My Free AuditServing California businesses — and email-driven desks anywhere in the U.S.