Build a location in minutes. Then make it convert.
Two custom apps for multi-location HighLevel operators, sitting on one shared platform layer. The first takes a new sub-account from blank to a reviewable draft in minutes instead of days. The second makes sure the leads that build generates do not die at the client's front desk.
01 — The problem
Two problems, and almost everyone only attacks the first
If you run a repeatable HighLevel build across a lot of sub-accounts, you have two of them. They are not the same problem, they do not have the same fix, and solving one without the other produces an expensive machine nobody uses.
Problem one
Getting a location live is slow The build is identical every time. The content inside it is different every time. So somebody sits down with the client's website open in one tab and HighLevel in the other and types about a hundred fields, one at a time, for days.
Problem two
Getting the location to use it is harder You can deploy a perfect build and still watch a third of the leads die at the client's front desk. Slow responses, no accountability, nobody watching the queue. And when those leads do not book, it looks like the marketing failed.
02 — What gets deployed
The journey inside every sub-account
One system covers the whole journey, from first enquiry through to repeat business, in six stages. Every message in it is a template with the location's own details slotted in — and that is what the hundred-odd custom values are: names, services, prices, hours, colours, fonts, policies, and copy that has to sound like this specific business.
Acquire
Capture and score the enquiry A new lead comes in, gets ranked by how ready they are, and gets worked until they book.
Attend
Warm them up before the appointment Booked but not turned up. Emails and texts run in the gap so they attend, and arrive ready to buy rather than cold.
Convert
The appointment itself They turn up and get a recommendation. They say yes, they say no, or they say they will think about it.
Recover
Chase the undecided "I'll think about it" is the biggest pot of recoverable money in most businesses, so it gets worked on its own track until they commit or drop out.
Advocate
Turn customers into advocates Once the job is done, reviews, referrals and testimonials get collected and pushed back to the top of the funnel.
Reactivate
Work the existing base Anyone who never booked, never turned up or said no gets picked back up later. Existing customers get matched to the other services they would genuinely benefit from.
03 — App one
The provisioning console
STEP 1
Location submitted with a domain and a name
STEP 2
Sources fan out, values come back scored
STEP 3
Operator reviews ~100 fields on one screen
STEP 4
Typed confirmation, then a logged, reversible push
No single source has everything, and every source is wrong about something. So the console does not ask one API for a profile and trust it. It fans out across a stack of narrow sources, each genuinely good at one thing, then reconciles what comes back.
Nothing arrives as a bare value. Every proposed field carries its source and a confidence score. The operator is not re-deriving every value from scratch — they are scanning provenance, accepting the fields where independent sources agree, and spending their actual attention on the handful the system has flagged as contested or thin. The system is not trying to be right. It is trying to be transparent about how confident it is, which is a much more useful thing for it to be.
Stage one — fan out across narrow sources
Context.dev
brand · styleguide · sitemap · extract Logo, palette and typography from nothing but a domain. Structured extraction pulls services and positioning into a schema I define. Google Places verified operational facts Address, opening hours, phone number, rating, review count, and the reviews themselves. Google autocomplete demand language What people actually type when they search for this business. Frequently not the language on its website. Perplexity unstructured research Who the people are, what they are known for, what has been written about them elsewhere. Companies House legal entity Registered name, company number, registered address. The trading name is regularly not the name that legally belongs at the bottom of an email.
Stage two — reconcile
Every source proposes values, and they disagree. The website gives one set of opening hours and Google gives another. The trading name differs from the registered name. The fonts on the live site differ from the ones in the brand guidelines. The merge is the actual engineering.
Stage three — one reviewable field, with its provenance
Contested
confidence 62% Opening hours Mon–Fri 08:30–17:30 · Sat 09:00–13:00 Google Places — verified Website — conflicts Two sources disagree, so the conflict is surfaced rather than silently resolved. This is where the operator's attention goes. Agreed confidence 98% Registered legal name HARBOUR LANE INTERIORS LTD Companies House — register Website footer — matches Independent sources agree, so the operator scans it and moves on. That is what makes reviewing a hundred fields realistic in one sitting.
There is a portal around it
Onboarding is a staged process, not a single event, so the console sits inside an admin portal that tracks every location through those stages. You can see at a glance what has been done, what is waiting, and where each pending client has got to, without going into HighLevel at all.
And a second way in
Some information is not on a website and never will be. So there is a managed client interview: you run the call, Fathom records and transcribes it, and the transcript populates custom values and other areas of the CRM directly. The discovery call stops being something you then transcribe by hand. It becomes the input.
04 — Safety
Why it cannot break your account
Automation that writes into a live sub-account is only useful if you trust it. Most of the build went into making it safe rather than fast.
RULE 01
It can only update, never create If a field does not already exist, the console reports it and moves on. Otherwise somebody deletes a field deliberately in HighLevel and the next run silently puts it back. The rule means the tool can never overrule a human decision made in the account.
RULE 02
A short, fixed allowlist of settings Ten specific location fields, decided in advance. Everything else is discarded before the request is built. Mail settings, phone configuration and snapshots are not on the list and cannot be reached.
RULE 03
Nothing pushes without a typed confirmation Four actions, four phrases you type out in full. The check runs on the server, not in the browser, so a stale tab or a double-click cannot fire a deploy.
RULE 04
Every change is logged with the old value Undo is one button, not an afternoon of reconstruction. That is the difference between something you run on a live client account and something you only ever test on a spare one.
05 — App two
FrontDesk Assist
The provisioning console builds the machine. FrontDesk Assist is what makes it pay.
All the data that journey generates is inert until someone acts on it, and HighLevel's native interface is not designed for a receptionist with a phone in one hand and a queue of callbacks in front of them. So FrontDesk Assist is a separate app installed into the sub-account that gives the front desk team the view their job actually needs.
Live queues
What needs doing right now, in order, rather than buried in a pipeline view. Overdue follow-ups turn red. Anything inside the first hour is flagged before anything else.
One contact, in full
Last message, open opportunity, stage, value, appointment and workflow state — without leaving the queue.
Put the clock on the wall and the leaderboard next to it
Priya S.
1m 40s
Marcus R.
3m 02s
Sofia M.
7m 18s
George F.
19m 44s
07 — The platform layer
The bit that made building the second app cheap
Both apps sit on the same foundation. The provisioning console established that plumbing; FrontDesk Assist reused it wholesale and only had to add its own interface and logic on top.
That is the part worth stealing. The first custom app is expensive because you are paying for OAuth, token handling, install and uninstall flows, webhooks and data sync. The second, third and fourth are cheap, because that work is already done and does not get rewritten.
Marketplace app install
Per-location OAuth & tokens
Webhooks & data sync
Backend & database foundation
08 — In practice
What it does, and what it deliberately does not
09 — Who this is for
Two ways to use what is already built
Any operator running a repeatable HighLevel build across a lot of sub-accounts, and any agency that generates leads for clients and then watches conversion happen somewhere they cannot see. The pattern both times: build the platform layer once, then put products on top of it.
Marketlinx
DIGITAL
Start here
Start with the audit
A written architecture record and a staged plan, useful whether or not I build the rest.