AI Automation Specialists for Service Businesses
The busywork ends here.
Tell us what's eating your time, what's still done by hand, or where things keep slipping through. We'll use automation and AI to build a smarter way to get it done.
GoHighLevelZapiern8nMakeAPIsAIWebhooksAcross every build to date
Our work
Real problems. Real systems.
Real businesses.
We don't automate things just because we can. We look for what's being missed, repeated, tracked by hand, or left to someone's memory, then build around that problem.
Voice AI Systems
Press play to hear a real AI cold call. The AI is calling, the lead is a real human, and no human caller is involved.
Real call recordings
Cold Call #1 — Outbound lead qualification
The AI makes the call and qualifies the lead. 2 minutes.
Cold Call #2 — Outbound call to booking
The AI makes the call, keeps the conversation going and books the appointment on the call. 3 minutes.
Real buildAI Agent for Facebook Page Inquiries
Answers questions sent to a Facebook page in seconds, using the business's own information, so enquiries don't sit waiting for someone to get online.
See how it works
Real buildAI-Powered CRM Summary Email
Every day, this system reviews the leads in the CRM and emails the team a clear written summary of what's happening, so the day starts knowing exactly which leads need attention.
See how it works
Real buildGmail Attachments Filed Automatically
Detects incoming attachments, reads them with AI, files them in the right Google Drive folder, logs them and tells the owner it's done.
See how it works
Real buildGoHighLevel at scale
100+ sub-accounts set up, automated and maintained. The deepest is a home remodeling company: a full audit and rebuild of a CRM nobody could trust.
See the full record of work
Real buildAutomated Sales & Client Onboarding Workflow
Automated lead follow-ups, quotes, onboarding, and post-sale communication, all based on where each lead is in the sales process.
See how it works
Real buildFacebook Page Scraper to Sheets
Collects the Facebook page data you actually asked for through Apify and logs it straight into Google Sheets. Research with zero copy-pasting.
See how it works
Real buildAutomated Financial Report Retrieval & Filing
Automatically retrieves and formats financial transaction data from Xero, then attaches the completed report to the right Asana task, eliminating manual downloading, formatting, and uploading.
See how it works
Real buildPayment-to-Pipeline Automation
A deposit paid in QuickBooks now moves the deal to the right stage in the CRM on its own, and tells the team it landed.
See how it works
Real buildLead Source Integration
Houzz can't send leads into GoHighLevel. Now every enquiry arrives as a lead with the right source, a deal and follow-up.
See how it works
Real buildWebsite Lead Activity Tracking
Tracking looked installed but had never recorded a visit. Since the fix, 1,878 visits have run through it.
See how it worksSystem Guide & Team Training
Everything about the system lived in one person's head. Now the team runs it from a plain-English guide and short videos.
See how it worksHave a different process in mind?
What’s taking up more time than it should?
If it’s repetitive, we can automate it. If it requires reading, deciding, or writing, we can bring AI into the workflow.
How we work
Good automation starts
before we build anything.
The best automation isn't the one with the most workflows. It's the one that makes the business easier to run.
- Where leads and jobs come from
- What's still done by hand
- What should stay with a person
- Where things stall or get missed
- Workflows and integrations across your tools
- AI for the reading, deciding and writing
- Checks so a silent failure can't hide
- Nothing published until it's tested
- A plain-English system guide
- Short videos, one task each
- Build sheets for anything left to switch on
- Every decision recorded with its reason
Why us
We understand the business process behind the automation.
Building a workflow is the easy part. Good automation means understanding what should happen before it starts and after it ends.
- Business first, technology second.Tell us the problem. Picking the workflow or the tool is our job.
- Automation without removing the human.Conversations and judgement stay with your team. The repetitive work doesn't.
- Built around your business.No templates. We learn your process, then build to it.
- Built to be understood.Documented in plain language, so it's never a mystery only one person understands.
Featured case study
Fixing a messy CRM
We took a CRM that was messy, unreliable and half-built, fixed what was broken, and automated every stage so follow-up happens without anyone having to remember.
Audit snapshot
Before changing anything, we checked the whole account, not a sample: 465 deals, 5,659 contacts, 691 tags and every automation.
What we did
- Stopped the messages that were hurting customer relationships.
- Cleaned the pipeline down to real deals only.
- Repaired the existing automations.
- Rebuilt 30+ emails on one design that displays correctly everywhere.
- Added automations to every stage, from first enquiry to finished job.
What the client was left with
- A CRM they can trust.
- Follow-up that runs without anyone having to remember it.
- A plain-English system guide and short training videos, so the team can run it on their own.
A full redacted audit is available on request.
The problem
- Messages were going to the wrong people.
- The pipeline was full of deals that weren't real.
- Emails looked broken on many phones and inboxes.
- Most stages had no automation, so follow-up depended on someone remembering.
What changed
- The owner can trust the pipeline numbers.
- Customers and opted-out contacts are no longer messaged by mistake.
- Every lead and customer gets consistent follow-up at every stage.
- Emails look professional in every inbox.
- The system is ready for the team to grow without breaking.
Proof: the same email, before and after
Emails that hold together in every inbox.
Both screenshots are the same email, opened in Gmail. The old one is nearly three times longer because the award badges broke into a giant stack.
- One branded design that looks the same everywhere, including Outlook and phones.
- 16 award badges now sit in two neat rows.
- Buttons that disappeared in Outlook now show everywhere.
- 30+ emails written, rebuilt or corrected, each tested on desktop and mobile.
The full record of work
Everything we found,
and everything we fixed.
Ten groups, in the order they were tackled. The damage first, because stopping it mattered more than building anything new.
Things that were actively doing damage6 fixes
- Stopped a text sequence that was messaging 195 people every two weeks, including customers in the middle of a build. The carrier had already sent a deliverability warning.
- Made unsubscribes work. 224 people had asked to stop and were still getting everything, because the label reps used didn't switch anything off.
- Checked all 413 deals one by one and protected 11 active customers, so they keep getting project and appointment email after opting out of marketing.
- Added exit rules on closed deals. Won, lost and abandoned now remove a contact from every marketing sequence. When 95 deals were later closed at once, all 95 came out cleanly.
- Cleared about $830,000 of pipeline that wasn't real: bulk-loaded cards from the old system that had never been verified. Every card triaged, and reversible.
- Stopped every lead workflow from also writing into an abandoned second system, so there's one source of truth.
Cleaning up the account5 fixes and 10 findings
- Reassigned contacts and deals from a salesperson who had left, so the system's tasks and alerts reach someone who actually works there.
- Found 195 of 198 open deals assigned to one person, and wrote every notification to go to the deal's owner with the owner as fallback, so it survives a second hire.
- Fixed intake workflows that branched on one rep's name. The day a second rep was added, their leads would have vanished silently.
- Corrected review emails whose links sent customers to a profile page, or to the wrong business entirely.
- Identified $5.1M of duplicate cards inflating the pipeline, and documented them so they can be excluded from any report.
- Explained the records that looked like a test form left running: they came in with an old import, not from a live form.
- Found a placeholder value the old system wrote instead of leaving a field blank, which hid 12 deals and 1,054 contacts from any “no source” report.
- Catalogued 691 tags, around 250 of them junk from the legacy import, so nobody builds reporting on a tag that turns out to be nothing.
- Cleaned junk values out of the lead source field and corrected tag names everyone had been using incorrectly.
- Found eight Facebook Group leads mis-tagged as paid ads, which was padding the paid-advertising number.
- Dated the two import events so it's clear which records automation can ever touch, and flagged that stage age can't be trusted after the rebuild.
- Flagged an old calendar and a second booking phone number so neither gets carried forward by accident.
Calendars and appointments5 fixes and 5 findings
- Built a calendar per appointment type. There had been one mixed calendar where every booking was 30 minutes, whether it was a phone call or a two-hour home visit.
- The in-home consultation is two hours with an hour of travel blocked either side. The discovery call is thirty minutes.
- Built every calendar so adding a new rep is a staff addition, not a rebuild.
- Set the meeting location per calendar, so the in-home pulls the customer's address instead of asking the rep to retype it.
- Built the showed / no-show link: a text after the meeting with two links. One tap sets the status, moves the deal and starts the follow-up.
- Documented why the old no-show tag could never work, so it goes into training rather than being engineered around.
- Built reminder sequences for both appointment types, by email and text, plus the internal alerts.
- Wrote the in-home preparation email, sent three days before: who's part of the decision, a rough budget, must-haves against nice-to-haves.
- Resolved duplicate stages across two boards, where a deal passing through both would have received everything twice.
- Decided self-booking per calendar: on for discovery calls so a no-show can rebook, off for home visits because the rep books those.
Leads and where they come from7 fixes and 6 findings
- Built the follow-up: welcome email inside 60 seconds, six emails over a fortnight, six call reminders, an owner alert on day 4 and a decision task on day 14.
- Every step checks the deal first, so the whole sequence stops by itself the moment the lead moves forward.
- Applied the same treatment across every intake form, not just the one that had it.
- Guarded the sequence so somebody who fills in two forms doesn't receive everything twice.
- Stopped workflows from overwriting finished projects when a past client came back, which was going to happen within weeks.
- Audited lead source across all 465 deals and 5,659 contacts, the full population rather than a sample, and graded all seven intake workflows.
- Found paid Facebook writing itself two different ways, splitting paid social across two report lines.
- Found that Houzz had no route into the account at all: 281 Houzz contacts, 280 from one old import.
- Found a LinkedIn workflow that had never run once, and Instagram leads arriving with no source.
- Traced fourteen leads created by an unidentified connected app that sets the source before any workflow runs.
- Separated the real blank-source rate from the import noise: 61% overall, but 24.5% ongoing, which is the number worth acting on.
- Wrote down the channel definitions so paid ads and the free Facebook group never get merged in a report.
The emails30+ written, rebuilt or corrected
- Built one house template that survives being sent, after finding the platform strips styling on send, so what arrived in an inbox wasn't what the preview showed.
- Fixed the footer of 16 award badges that stacked, broke or dropped depending on the email client.
- Rebuilt every call-to-action button so it shows up in Outlook, which renders the old approach inconsistently or not at all.
- Fixed a headline that pushed the email off the screen on phones, found by an automated overflow test rather than by eye.
- Rebuilt six review emails so a click is actually recorded and can start a follow-up. Every link in them had been hardcoded.
- Wrote a three-part series explaining the company's 8-step process, plus a single version reps can send to one prospect.
- Wrote four nurture emails for the stage where projects quietly die, aimed at the real reasons people stall.
- Wrote ten past-client emails at six, twelve, eighteen and twenty-four months plus seasonal, with 30 real project photos placed across the set.
- Wrote the welcome sequence, the in-home preparation and thank-you emails, the discovery call thank-you, the post-consultation follow-up, the check-in nudge, the feedback email and the deposit-paid email.
- Checked every email for overflow at desktop and phone widths, re-run after every copy change, plus structural checks on unsubscribe links, merge tags and badge counts.
How the workflows are built7 fixes and 8 standards
- Built stall nudges on the four stages where deals die. A $400,000 job had once sat in one stage for over a month with nobody told.
- Set every threshold from what the owner said the real cycle time was, rather than guessing, and retired the old spec so nobody builds from it.
- Worked around a pipeline column doing two different jobs, using two tap-links so a healthy deal in revisions can be told apart from one that has gone quiet.
- Deliberately left the post-visit recap as a task with the email already drafted, because the reps' own recaps are what converts.
- Fixed a timing contradiction between a text that said now and a task due the next day.
- Tied escalation to deal value: the second nudge copies the owner, and deals over $250,000 escalate immediately.
- Documented that internal texts fail silently if a user has no phone number on their profile, and wrote it into the prerequisites for every build.
- Set send windows on every internal notification, so nobody gets a work text at 3am.
- Used cooldown tags so one person browsing five pages doesn't produce five alerts.
- Wired every condition with both branches explicit, so no lead is ever silently dropped.
- Added stop-on-reply to every nurture sequence.
- Assigned every task to the deal's owner rather than a named person, and gave every task a due date so it appears in a daily list.
- Wrote test plans for each build: click-through, tag, date stamp, text, task due date and second-click behaviour, step by step.
Reviews and closing a job out8 fixes and 10 findings
- Built a closeout that actually asks. 86 jobs had been completed and only 3 had ever reached a review stage. The system had never sent a single request.
- Four stages at the end of the board: a private project-manager review, then a short survey, then the public ask, then a follow-up offer.
- Built a low-score alert on any single answer below four stars, which emails the owner straight away and holds the public request for a few days so somebody can call first.
- Flagged the original plan as review gating, which is against Google's policy and covered by the FTC's rule on consumer reviews, and designed an alternative that gets the same protection legally.
- Costed the $200 review incentive nobody had run the numbers on: $6,800 per 86 jobs at even a 40% review rate, and set out three options with the exposure of each.
- Rebuilt review links that would have expired, and verified each one resolves to the right business.
- Worked around the platform's one-review-link limit for a company running two business lines, with a branded router page per division.
- Settled the division of labour between two systems that would otherwise have asked every customer for a review twice.
- Caught a whole batch of review emails using plain web addresses, which record nothing, before they went live.
- Specced the review-click notification, kept the gift link separate as real evidence, and deliberately left the payout manual.
- Set a ceiling on the asking: three emails and then a phone call.
- Established that reviews often can't be matched automatically, because people review under a nickname or a spouse's account, and turned it into one habit instead of an engineering problem.
Found by digging6 findings
- Found website tracking that had been installed and verified, and had never sent a single event. The install method silently dropped the setting the tracker needs.
- Diagnosed it from outside the account by reading the published tracking container directly, without waiting on anyone's access.
- Found that the platform's quiz scoring ignores star ratings entirely: a form answered with nothing but five stars scored zero.
- Established that a total score can't say nothing was bad, so the alert tests for the bad answer instead of the good average.
- Established that appointment data from the API can't be trusted as evidence, so no conclusion in the analysis rests on it.
- Documented the platform limits that shape every build: no API for workflows, no API for bulk do-not-contact, and a known builder bug that drops filters when a trigger is saved.
What the team was left with5 deliverables
- The System Guide: every stage on all three boards, in the order a job moves through them, with what it means, what happens automatically, what a person still has to do, and how the deal moves on.
- Screen-recorded training videos made in the live account, one job per video, plus a full walkthrough of the whole system.
- Videos named the way somebody would search for them, kept in one place in watching order, with recording dates so it's obvious when one goes stale.
- Click-by-click build sheets for everything not yet switched on, written so somebody who wasn't in any meeting can build it.
- Every judgement call written down with its reasoning, so a future change is a decision rather than an accident.
The rules we put in place17 standing rules
- Look for an existing open deal before creating one, so a returning client never overwrites a finished project.
- Never leave a branch ending in nothing. That's a silently dropped lead.
- Guard any sequence that allows re-entry with a tag, so nobody gets duplicate emails.
- Send tasks and notifications to the assigned user, never to a person by name.
- Automate what's identical for everyone. The rep writes anything with their own numbers in it.
- Validate a threshold against real time-in-stage before shipping an alert.
- Test any platform's scoring with a deliberately lopsided answer before designing around it.
- Test for the bad case, not the good one.
- Stop on reply, on every nurture sequence.
- One automated text before a contact engages, then email and a phone call. Never text dormant contacts.
- Every email inline and tested with a real send, because the preview doesn't reflect what arrives.
- Every review call-to-action is a trigger link, never a plain web address.
- Never use a copy-pasted search address as a permanent link. They expire, and nothing tells you when.
- Build one workflow at a time and publish it before starting the next.
- Don't rename forms and never delete a calendar. Both rewrite history you can't get back.
- Record training against a test contact, and name each video the way somebody would search for it.
- Don't make a permanent change on a guess. Park it and ask.
Case study
Website tracking fix
Many businesses have tracking that looks installed but isn't recording anything. We check it and fix it.
The problem
- Tracking was set up to show when a lead came back to the website, a strong sign they're ready to buy.
- It showed as installed, but it had never recorded a single visit.
- Nothing looked broken, so nobody knew.
What we built
We found the cause without needing access to their tracking account: the way it was installed silently stripped out a setting the tracker needs to start. We reinstalled it in a way that works.
How it works
- A lead visits the company website.
- The visit is now recorded against their contact.
- The rep gets an alert that the lead is back. Repeat visits within a few days count as one alert, so there's no spam.
What changed
- Website visits are recorded against each contact.
- Reps can see when a lead is back on the website and call at the right moment.
Proof: the actual build
Live in the account.
Case study
System guide and training videos
We don't just build it. We make sure your team can run it without us.
The problem
- Everything about how the CRM worked lived in the head of whoever built it.
- A new team member, or the next person to take over, would have been guessing.
- Guessing safely means changing nothing, so the system slowly falls behind the business.
What we built
A plain-English guide to the whole system, short training videos recorded inside the live account, and step-by-step build instructions for anything not yet switched on.
How it works
- The guide walks through every pipeline stage in order: what it means, what happens automatically, what a person still has to do, and how a deal moves on.
- A full walkthrough video covers the whole system.
- Short videos, one per task, cover jobs like booking a home visit or marking a no-show. Each is named the way someone would search for it.
- Build sheets let someone else finish the remaining work without having been in any meeting.
- Every decision is written down with the reason behind it.
What changed
- The team can run and troubleshoot the system without the person who built it.
- New staff can learn one task in a few minutes.
- Future changes are deliberate decisions, not accidents.
Case study
QuickBooks payments into the CRM
When a customer pays, the CRM should know, and the deal should move. We connected QuickBooks to GoHighLevel so both happen the moment the money lands.
The problem
- Customers pay three different deposits over the life of a project: design, lock-in and ordering. Each one means the job is ready for its next stage.
- Payments were recorded in QuickBooks, but the CRM had no idea.
- A sales rep had to notice each payment and move the deal card by hand. If nobody did, the pipeline showed paid jobs sitting in the wrong stage.
What we built
A connection between QuickBooks and GoHighLevel, built with Zapier. When a deposit is paid, Zapier works out which of the three deposits it is and passes it to the CRM.
A separate automation for each deposit then tells the team, moves the deal to the right stage and logs the payment on the record.
How it works
- A customer pays a deposit in QuickBooks.
- Zapier picks up the payment and works out which deposit it is.
- It updates the customer in GoHighLevel and flags which deposit was paid.
- The team gets an email and a text straight away.
- The system finds the customer's deal and moves it to the next stage. If there's no deal yet, it creates one, so no payment is ever left without a card.
- A note is added to the record. After a design deposit, the customer also receives the next-step email automatically.
What changed
- Deals move to the right stage the moment a deposit is paid. Nobody has to move cards by hand.
- The team hears about every payment immediately, by email and text.
- Every payment ends up on a deal card, even if the deal was never created in the CRM.
- Accounting and sales now work from the same information.
Proof: the actual build
What's running behind the scenes.
Case study
Houzz leads into the CRM
Houzz was one of the company's key lead sources, and none of those leads were reaching the CRM. We built the missing route, so every Houzz enquiry gets the same treatment as any other lead.
The problem
- Houzz can't send leads directly into GoHighLevel.
- Of 281 Houzz contacts in the CRM, 280 came from one old import. Only one had arrived since.
- New Houzz enquiries sat in email notifications instead of the CRM, so they missed the follow-up every other lead got, and nobody could see how many leads Houzz was bringing in.
What we built
A route that turns Houzz's lead notification emails into CRM leads. Every notification is forwarded to Zapier, which creates the contact in GoHighLevel with Houzz recorded as the lead source.
Inside the CRM, an automation then creates the deal, assigns a rep, alerts the team and starts follow-up, without ever creating a duplicate.
How it works
- A homeowner sends an enquiry through Houzz.
- Houzz's notification email is forwarded automatically to Zapier.
- Zapier checks it's a genuine lead notification, pulls out the name and phone number, tidies them up, and creates the contact in GoHighLevel with Houzz marked as the source.
- The CRM checks whether this person already has a deal. If they do, it stops, so nobody is duplicated.
- If not, it creates a new deal, assigns it to a rep and alerts the team.
- The lead is added to follow-up. If Houzz hasn't passed on an email address yet, the system waits until one is added, then starts.
What changed
- Houzz leads land in the CRM on their own instead of waiting in an inbox.
- Every Houzz lead gets a deal, a rep and follow-up, the same as leads from any other source.
- Every Houzz lead is labeled correctly, so the owner can see what the channel is really worth.
- No one has to copy lead details from an email into the CRM.
Proof: the actual build
What's running behind the scenes.
Built to handle the awkward cases
- Other Houzz emails: only real lead notifications get through, so nothing else turns into a fake lead.
- Repeat enquiries: if the person already has a deal, nothing is duplicated.
- Missing email: Houzz doesn't always pass on an email address straight away. The system waits for one instead of failing or sending nothing.
- Correct source: every lead is labeled as Houzz, so reports finally show the channel's real numbers.
Case study
Automated Sales & Client Onboarding Workflow
Automated lead follow-ups, quotes, onboarding, and post-sale communication, all based on where each lead is in the sales process. Their pipeline lives in Asana, so moving a task to the next column is all it takes.
The problem
- The whole sales process ran as columns in Asana, and every step after a card moved was done by hand.
- Folders had to be created, quiet leads chased, quotes followed up, welcome emails written and aftercare remembered.
- Whether a client heard from them depended on who was busy that week.
What we built
Five automations, all hanging off one thing: a task changing column in Asana.
Zapier reads the new status, takes the matching path, and does the work that used to sit on somebody's list.
How it works
- Ready to start. A Google Drive folder is created and named after the lead, and a "Social Media Content" subtask is added to their task with a link to that folder.
- No response. Follow-ups keep going out until the client replies, escalating rather than stopping after one try.
- Quoted. A follow-up on the quote goes out once a week, so a sent quote is never left sitting.
- Approved. The client gets a welcome email with a personal message and the PDF attached.
- Paid and closed. An aftercare recommendation email goes out, in one of three versions depending on which service was installed.
What changed
- Moving a card is now the only manual step. The rest follows from it.
- No lead goes quiet unnoticed, and no quote is left without a follow-up.
- Every client gets the same welcome and the right aftercare for what they bought.
- Project folders and subtasks exist before anyone has to look for them.
Proof: the actual build
One trigger, five paths.
Case study
Automated Financial Report Retrieval & Filing
Automatically retrieves and formats financial transaction data from Xero, then attaches the completed report to the right Asana task, eliminating manual downloading, formatting, and uploading.
The problem
- Every time a job was finished, somebody had to log into Xero, run the report, download it, tidy the file and upload it to the right task.
- The report they wanted isn't available through Xero's API at all, so the obvious automation wasn't possible.
- Until it was filed, the record of that work sat in somebody's downloads folder.
What we built
A Make scenario that runs the moment a task is marked complete in Asana.
Since the report itself can't be pulled directly, it pulls the underlying transaction data instead and rebuilds the file to match what a person gets when they download it by hand.
How it works
- A task is marked complete in Asana.
- The scenario connects to Xero and pulls the transaction-level data for the full calendar year.
- Each transaction is written into a spreadsheet, which assembles the file row by row in the same layout as the manual download.
- The rows are gathered back into one CSV file.
- The file is attached to the completed task in Asana.
- The spreadsheet is cleared, ready for the next run.
What changed
- No logging in, running, downloading, reformatting or uploading.
- The report is filed against the right task, every time, without anyone chasing it.
- A platform limit that would have killed the idea was worked around rather than accepted.
Proof: the actual build
The scenario, end to end.
Case study
AI Agent for Facebook Page Inquiries
Answers questions sent to a Facebook page in seconds, using the business's own information, so enquiries don't sit waiting for someone to get online.
The problem
- Questions arrive on the Facebook page at all hours, and most of them are the same handful of questions.
- Whether somebody got an answer depended on who was online and how busy the day was.
- A slow reply on social media usually means the person has already messaged a competitor.
What we built
An AI agent, built in n8n, that sits behind the Facebook page and answers enquiries itself.
It doesn't make things up: every answer is drawn from the company's own knowledge base document, so what it says is what the business would say.
How it works
- Someone sends a question to the Facebook page.
- The message arrives at the automation instantly, and Facebook's own connection check is answered automatically so the link never drops.
- The agent pulls the business's knowledge base document.
- The language model writes the reply from that document, and remembers the conversation so far, so a follow-up question still makes sense.
- The answer is sent straight back to the person on Facebook.
What changed
- Enquiries get an answer in seconds, at any hour, without anyone watching the page.
- Answers stay consistent, because they come from one document rather than whoever replied.
- Updating that document updates what the agent says. No rebuild needed.
- The team only picks up the conversations that genuinely need a person.
Proof: the actual build
The agent, end to end.
Case study
AI-Powered CRM Summary Email
Every day, this system reviews the leads in the CRM and emails the team a clear written summary of what's happening, so the day starts knowing exactly which leads need attention.
The problem
- Knowing where the leads stood meant logging in, digging through records and piecing a picture together by hand.
- Nobody does that every morning, so leads waiting on a reply went unnoticed for days.
- The information was all in the CRM. It just never reached the people who needed it.
What we built
A daily summary that writes itself and lands in the team's inbox.
It reads the CRM, works out what changed and what is overdue, and explains it in plain English rather than as a table of numbers.
How it works
- The automation runs on a schedule, every day.
- It pulls the current leads straight from the CRM.
- It works out which are new, which are still waiting for a response, and where follow-up is falling behind.
- The language model writes that up as a short, readable summary.
- The summary is emailed to the team, ready before the day starts.
What changed
- Nobody logs in, digs through records or builds a report by hand.
- The team starts the day knowing exactly which leads need attention.
- Leads waiting on a reply surface the next morning instead of next week.
- Fewer opportunities slip through the cracks.
Proof: the actual build
The daily run.
Case study
Gmail Attachments Filed Automatically
Detects incoming attachments, reads them with AI, files them in the right Google Drive folder, logs them and tells the owner it's done.
The problem
- Documents arrive by email all day, and somebody has to download each one and drop it in the right folder.
- It only takes one busy afternoon for files to end up in the wrong place, or nowhere at all.
- Nobody could say what had come in without going back through the inbox.
What we built
An automation that watches the inbox and handles every attachment the moment it lands.
It doesn't just dump files in one folder. It reads each one first, so it knows what the document actually is and where it belongs.
How it works
- A new email with an attachment arrives.
- The file is passed to AI, which reads it and works out what it is.
- It's uploaded to the right folder in Google Drive, named so it can be found later.
- A row is added to a spreadsheet, so there's a running log of everything received.
- The owner gets an email confirming what came in and where it went.
What changed
- Nobody downloads, renames or files attachments by hand.
- Documents land in the right folder the moment they arrive, not whenever someone gets to the inbox.
- There's a log of every file received, so nothing has to be reconstructed from email later.
- The owner knows it happened without checking.
Proof: the actual build
Inbox to Drive, in one run.
Case study
Facebook Page Scraper to Sheets
Collects the Facebook page data you actually asked for through Apify and logs it straight into Google Sheets. Research with zero copy-pasting.
The problem
- Building a list meant opening page after page and copying details into a spreadsheet by hand.
- It takes hours, and by the time the list is finished the first entries are already out of date.
- Typing things across also means typos, missed fields and rows that don't line up.
What we built
A scenario that takes the list of pages from a spreadsheet, collects the data, and writes it straight back into the sheet.
It pulls only the fields that were asked for, so the sheet stays usable instead of becoming a dump of everything a page holds. Run it again whenever the list needs refreshing.
How it works
- The scenario reads the pages to look up from a spreadsheet.
- It hands them to the scraper and waits for the run to finish.
- The results come back and are split into individual records, keeping only the fields that were asked for.
- Each record is written into the sheet as its own row.
- Anything that doesn't fit the expected shape is logged separately, so nothing is quietly dropped.
What changed
- No copy-pasting, and no typos from retyping.
- A whole list is collected in one run instead of an afternoon of tabs.
- Only the data asked for lands in the sheet, ready to sort, filter and work from.
- Refreshing the data is running it again, not starting over.
Proof: the actual build
List in, rows out.
Questions
Questions we get a lot.
Short answers. Ask us anything else.
Do I need to know what automation I need?No
No. Tell us what's taking too long, what's done by hand, or where things slip through. Working out what should happen automatically is our job, not yours.
Do I have to change the tools I use?Usually not
Usually not. Most of our work connects and improves what you already pay for. If a tool genuinely can't do what you need, we'll say so rather than build a workaround that breaks later.
What if my CRM is a mess?Common
That's where a lot of our work starts. We audit every contact, deal and automation first, fix what's broken, and only then build on top. Automating a messy system just makes the mess faster.
Will this replace my team?No
No. We automate the repetitive work around the parts that need a person. Real conversations, judgement calls and relationships stay with your team, and they get more time for them.
What happens if something breaks?We see it
Builds are tested path by path, including the awkward cases, before anything goes live. Where a failure would be silent, we add a check so it surfaces instead of disappearing.
What am I left with at the end?A system you own
Everything documented in plain language, your team trained on it, and the reasoning behind each decision written down. You can run it, change it or hand it to someone else without us.
Ready to automate what's slowing you down?
You don't need to know what automation you need.
Tell us what's happening now.
We'll show you what can be automated, what should stay personal, and how it fits together.