What we can build.

An AI dispatcher for a mid-sized freight operation.

The kind of problem

Dispatchers fielding 80–100 calls and texts a day from drivers. “What’s my next pickup?” “Where do I park overnight?” “Customer is asking about ETA.” Most of it is information already in the TMS, but drivers can’t easily get to it from the cab.

What we’d build

A text-message AI dispatcher tied into your TMS. Drivers text any question and your AI employee pulls the relevant data, formats it for a phone screen, and replies in seconds. If they can’t answer (mechanical issue, customer dispute, anything safety-related), they page a human dispatcher with the conversation context already attached.

Why it works

Drivers get answers in 10 seconds instead of waiting on hold. Dispatchers only see the calls that actually need them. A purpose-built AI dispatcher can comfortably handle tens of thousands of messages a month, with safety-critical situations always escalated.

An AI host for a multi-location restaurant group.

The kind of problem

Hosts too busy on the floor to take phone reservations during service. Calls go to voicemail. Voicemails get returned the next morning, by which time the caller has booked somewhere else. A 12-location group can lose 30–50 reservations a week this way.

What we’d build

A phone host who picks up on the third ring when no human can. Knows the menu, knows the floor plan, knows allergens, books directly into Resy or OpenTable. Sounds natural, transfers to a human host on request. Calls are transcribed and sent to the manager nightly so they can see what was handled.

Why it works

Captures bookings that were straight-up disappearing. Doesn’t replace human hosts during service, just covers the gap when they can’t pick up. A well-tuned voice teammate can handle most regulars without them noticing the difference.

An AI intake coordinator for a specialty clinic.

The kind of problem

The first five minutes of every new-patient appointment is often the doctor reading a chart they haven’t seen and asking baseline history questions the patient already answered on a paper form. Net effect: shorter actual examinations, longer days, frustrated patients.

What we’d build

An AI intake coordinator who texts new patients the day before their appointment, walks them through a structured history conversation, summarizes the relevant findings into a clinical-style note, and drops it into the EHR before the patient walks in. The doctor reviews the summary in 90 seconds before each appointment instead of building it from scratch.

Why it works

Patients prefer texting at their own pace over filling forms in the waiting room. The doctor walks in already oriented. Nine minutes a patient adds up across a full day. Built to your HIPAA obligations from day one.

An AI drafter for a mid-sized law firm.

The kind of problem

Attorneys spending hours each week drafting routine engagement letters, fee proposals, and client onboarding emails. The work is repetitive, the templates exist, but every document still gets customized by hand.

What we’d build

An AI drafter accessible from a Slack channel. Attorneys describe the engagement in plain English, your AI employee drafts the document using firm-approved templates and house style, the partner reviews and signs off. Every draft logged for the firm’s records.

Why it works

First-draft work, gone. Attorneys spend their time on the parts that actually require their judgment. House style stays consistent because your AI drafter is trained on years of approved documents. Time previously spent on admin becomes billable.