How Our AI Workflows Are Structured

Challenge

Enquiries arrived across four different channels at all hours. Agents were manually copying buyer details into spreadsheets, and by the time anyone replied, many buyers had already messaged a competitor. Site visits were arranged through back-and-forth phone calls that ate up a large part of the sales team’s day.

Solution

Every channel was connected to a single AI WhatsApp agent trained on the brokerage’s active listings and qualification criteria. The agent asks the right questions, recommends matching properties, and only hands a conversation to a human agent once a buyer is genuinely qualified and ready to move forward.

Implementation

We mapped the existing sales process with the team, defined clear qualification rules covering budget, location, timeline and property type, connected the agent to the CRM and calendar, and ran a two-week supervised pilot on a single branch before rolling it out across the other two.

Before → After

Illustrative only — not measured client results.

Technology

Challenge

Writing consistent, SEO-friendly product descriptions for every new SKU was close to a full day’s work each week. On top of that, the same handful of order and delivery questions arrived on WhatsApp and email dozens of times a day, pulling the founder away from sourcing and growth work.

Solution

AI now drafts product titles, descriptions and tags directly from supplier sheets and photos, with a quick human review step before anything is published. A connected support assistant answers order-status, sizing and return questions using live order data, and hands off anything unusual to the team.

Implementation

We built a lightweight review queue so the team could approve or tweak AI-drafted listings in minutes rather than writing from scratch, and connected the support assistant to the store’s order database so its answers stayed accurate as orders moved through fulfillment.

Before → After

Illustrative only — not measured client results.

Technology

Challenge

Documents arrived in inconsistent formats from different channels, and a staff member spent a significant part of each morning manually sorting, renaming and routing files to the right case before any real work could begin.

Solution

An automated intake pipeline reads incoming documents, classifies them by type, extracts key fields, and routes each one to the correct case folder and reviewer, with low-confidence documents flagged for a quick human check instead of being silently misfiled.

Implementation

We started with the three most common document types, tested extraction accuracy against a sample of past files with the team, and expanded coverage gradually rather than trying to automate everything from day one.

Before → After

Illustrative only — not measured client results.

Technology

Challenge

Phone lines were constantly busy during peak hours, appointment no-shows were common, and new patients filled out intake forms on paper that then had to be typed into the clinic’s system by hand.

Solution

Patients can now check availability and book appointments through WhatsApp or the clinic’s website, with automated reminders sent ahead of each visit and a digital intake form that feeds directly into the patient record.

Implementation

We worked within the clinic’s existing scheduling software rather than replacing it, connecting automation on top so staff kept the tools they were already comfortable with while removing the repetitive manual steps.

Before → After

Illustrative only — not measured client results.

Technology