5 QUICK AI WINS FOR YOUR BUSINESS.

Pick your industry. Get 5 practical AI workflows with real prompts, time-saved estimates, and setup tips. No email required.

5 quick AI wins for real estate agencies.

For sales agents, principals, and property managers.

[01]

Pre-listing presentation in 30 minutes

Suburb data + 3 recent comparables + your agency's track record → AI assembles the full pitch deck in your branded template. Agents spend 2–3 hours on these per appraisal.

Time saved
~2.5 hrs per listing presentation
Tool
Claude with your slide template + agency stats in a Project
$ Starter prompt+
Build a 6-slide listing presentation for [vendor name] at [address]:

Slide 1 — Cover (address, vendor name, today's date, your agent details)
Slide 2 — Suburb snapshot (median, days on market, recent 12-month trend)
Slide 3 — Three comparable sales (price, key features, sale date)
Slide 4 — Suggested price range with rationale
Slide 5 — Marketing plan + timeline
Slide 6 — Why [agency name] (use track record stats in the template)

Use the brand voice and slide structure from the template uploaded to this project. Don't invent numbers.

DATA: [paste suburb stats + comparables + your agency stats]

Tip:Build a template doc once with your agency's track record, brand voice, and slide structure. AI fills it in every time.

[02]

Buyer matching from new listings

Match every new listing against your full buyer database. AI flags which buyers should see what, with a one-line rationale per match. Skips lukewarm matches.

Time saved
~5 hrs/week of agent time
Tool
Claude / ChatGPT with structured data
$ Starter prompt+
From the buyer list and new listings below, output a table with three columns: LISTING, BUYER, WHY THIS MATCH.

Only include matches where bedrooms, suburb, and price band all align. Skip lukewarm matches.

BUYERS: [paste CSV]
LISTINGS: [paste CSV]

Tip:Update buyer preferences quarterly. Out-of-date data ruins the matching quality more than anything else.

[03]

Weekly market briefs for past clients

Personalised weekly market update sent to every past client based on their suburb, price range, and life-stage. Keeps you top-of-mind for the next referral.

Time saved
~3 hrs/week
Tool
Claude (with Perplexity for current data)
$ Starter prompt+
Draft a 150-word market update email for [client name], who bought a [bedrooms] home in [suburb] in [year]. Cover:

- One recent sale nearby (price + brief context)
- One market trend relevant to their property type
- A single line on what it means for them (no pressure)

End with: "Let me know if you'd like a current appraisal."

Tip:Keep a 'client preferences' doc in your workspace so AI always has the context.

[04]

Vendor open-home recap reports

After every open home, AI drafts a recap for the vendor from your voice notes — attendees, feedback themes, suggested next step.

Time saved
~15 min per open home
Tool
Claude with voice-to-text (or ChatGPT)
$ Starter prompt+
Below are my voice notes from today's open home at [address]. Draft a 200-word recap for the vendor covering:

- Number of attendees + buyer profile
- 2–3 feedback themes
- One recommendation for the next campaign step

Tone: honest, professional, brief.

NOTES: [paste]

Tip:Record voice notes in the car right after the open. AI handles the cleanup.

[05]

Email triage on inbound enquiries

AI reads every 'I saw this listing' email and drafts a personalised reply with viewing times and a buyer-qualification question. Drafts only — you press send.

Time saved
4–6 hrs/week across the team
Tool
Claude + Gmail OR ChatGPT
$ Starter prompt+
For each enquiry email below, draft a reply that:

- Thanks them by name
- Suggests the next 2 open-home times for that property
- Asks one qualification question (finance pre-approval / timeline / current living situation)
- Sounds like a human agent, not a template

Sign off as [your name], [agency name].

ENQUIRIES: [paste batch]

Tip:Never auto-send. Drafts only. A bad reply costs more than the time saved.

Want these built into your business?
We set up the whole AI workspace for you.
See packages

5 quick AI wins for mortgage brokers.

For sole brokers and small broker offices.

[01]

Compliance doc auto-drafting

Your fact-find, NCCP docs, and credit guides drafted from client info using your firm's house templates. Frees up the most expensive hours in your week.

Time saved
~2 hrs per application
Tool
Claude with your templates uploaded as project knowledge
$ Starter prompt+
Using the templates uploaded to this project, draft a first-pass [Fact Find / NCCP statement / Credit Guide] for the following client. Flag anywhere I need to add detail manually.

CLIENT INFO: [paste]

Tip:Always review against your compliance manual. Never skip the QA pass — your licence is on the line.

[02]

Pre-approval document screening

Client uploads docs. AI checks completeness against a per-lender checklist, flags what's missing, and drafts the 'still need these' email.

Time saved
~30 min per file
Tool
Claude with vision (PDF reading)
$ Starter prompt+
Review the attached client documents against the [lender name] checklist in this project. Output:

1. What's present and good
2. What's missing
3. What's there but needs clarification
4. A polite email to the client requesting the missing items

DOCS: [attach PDFs]

Tip:Build a 'lender checklists' workspace doc — one per major lender. Updates quarterly.

[03]

Personalised lender shortlist per client

Given a borrower profile + property, AI ranks 3 lenders from your panel with rationale (rate, policy, turnaround). Replaces 45 minutes of mental cross-referencing.

Time saved
~45 min per client
Tool
Claude / ChatGPT
$ Starter prompt+
Given the borrower profile below and the lender preferences doc in this project, rank the top 3 lenders for this scenario. For each:

- Why they're a fit
- Current best-fit product + rate range
- Expected approval turnaround
- One risk or watch-out

BORROWER: [paste]
PROPERTY: [paste]

Tip:Maintain a 'lender preferences' doc covering your panel — current policies, niches, turnaround speeds.

[04]

Weekly rate change digest for client portfolio

AI compiles which rate changes (across your panel of lenders) affect which clients in your book, with personalised messaging suggestions per client.

Time saved
~3 hrs/week
Tool
Claude + Perplexity for current rates
$ Starter prompt+
Below is my client portfolio and this week's lender rate changes. Produce:

- A summary of which changes affect which clients
- A draft 80-word personalised note to each affected client
- A priority list of who needs a call (vs. an email)

PORTFOLIO: [paste]
RATE CHANGES: [paste / link]

Tip:Run Monday morning. Schedule sends through the week so it doesn't look like a batch.

[05]

Client intake → borrower profile summary

Client fills out your intake form. AI summarises the borrower into a tight one-pager with risk flags before you spend an hour on it.

Time saved
~45 min per new client
Tool
Claude / ChatGPT
$ Starter prompt+
From the intake below, produce a one-page borrower summary covering:

- Income picture (PAYG, self-employed, combined)
- Existing debts and serviceability stress points
- Property goals and timeline
- 3–5 risk flags or items needing clarification

Keep it scannable. Use bullet points.

INTAKE: [paste]

Tip:Use a structured intake form (Typeform / Google Form) so the data comes in clean.

Want these built into your business?
We set up the whole AI workspace for you.
See packages

5 quick AI wins for financial advisors.

For advisors, paraplanners, and practice managers.

[01]

SOA first-draft generation

Intake form + recommendations + research notes → first-draft Statement of Advice in your house style. You QA, polish, and ship. Saves the equivalent of half a paraplanner per week.

Time saved
3–4 hrs per SOA
Tool
Claude with your SOA template + style guide in a Project
$ Starter prompt+
Using the SOA template and style guide in this project, draft a first-pass SOA for the client below. Cover all required sections. Flag anywhere I need to add detail. Do NOT invent figures.

CLIENT: [paste profile + recommendations]

Tip:First draft only. Human review is mandatory. AI hallucinations on financial figures = career-ending.

[02]

Cross-client opportunity detector

New tax law, market event, or regulation change → AI scans your whole client book, flags exactly which clients are materially affected, and drafts a personalised 'here's what this means for you' email per client.

Time saved
~4 hrs per major event
Tool
Claude with your client book + tags in workspace
$ Starter prompt+
New event: [paste tax change / market event / regulation update]

From the client book in this project, identify:

1. Clients MATERIALLY affected (income, holdings, life stage)
2. Clients AT THE EDGE (worth a check-in but not urgent)
3. Clients NOT affected (don't email — protects your inbox credibility)

For each materially affected client, draft a 150-word personalised email covering:
- What changed (one line)
- Why it specifically matters to them
- Suggested next action (book a chat / wait and see / specific to-do)

Tip:Tag your CRM export thoroughly (life stage, asset class, business owner y/n). Sharper tags = sharper targeting.

[03]

Compliance disclosure review on advice

Before you send advice, AI reviews against required disclosures (BID, FDS, ROA requirements) and flags gaps with suggested wording fixes.

Time saved
~20 min per piece of advice
Tool
Claude with your compliance manual uploaded
$ Starter prompt+
Review the drafted advice below against the compliance checklist in this project. Output:

- ✓ Items present and adequate
- ⚠ Items present but light on detail
- ✗ Items missing entirely
- Suggested wording fixes

ADVICE: [paste]

Tip:Keep an audit trail. Save each AI check log alongside the advice file.

[04]

Daily client comm digest

AI scans your CRM activity and drafts a list of which clients need a check-in today, what type of touchpoint, and drafts the actual emails.

Time saved
~1 hr/day
Tool
Claude + CRM export
$ Starter prompt+
From the CRM activity log and client lifecycle map below, produce a daily action list:

- Which clients are overdue for a check-in
- Suggested touchpoint type for each (call / email / no contact needed)
- Drafted email for any that I should send today

LOG: [paste]

Tip:Keep a 'client lifecycle map' doc — annual review cadence, life events to watch, communication preferences.

[05]

Portfolio review summaries

Quarterly review data → personalised review letter draft in your house voice for each client. Same depth, fraction of the time.

Time saved
~2 hrs per client
Tool
Claude with your client knowledge in a Project
$ Starter prompt+
Draft a 400-word quarterly review letter for [client name]. Cover:

- Portfolio performance vs. their target (be specific)
- One thing that worked, one that didn't (honest)
- Recommended actions for the quarter ahead
- Sign-off in [your name]'s voice

Use the client preferences doc in this project for tone.

DATA: [paste portfolio summary]

Tip:Build a 'client tone preferences' doc — formal vs warm vs technical per client.

Want these built into your business?
We set up the whole AI workspace for you.
See packages

5 quick AI wins for trades businesses.

For builders, plumbers, electricians, plasterers, landscapers.

[01]

Material take-off from plans

Upload architectural plans (PDF or photo). AI extracts quantities — concrete cubic m, timber lineal m, fittings count — into your costing template format. Estimators charge $100/hr+ for this.

Time saved
2–4 hrs per quote
Tool
Claude with vision + your costing template in a Project
$ Starter prompt+
From the plans attached, produce a material take-off in the costing template format in this project. Include:

- Concrete (cubic m) by element (slab, footings, etc.)
- Timber (lineal m, by size)
- Steel reinforcement
- Plasterboard (sqm)
- Fittings (count by type)
- Anything else relevant to a [job type] quote

Flag anything ambiguous from the plans. DO NOT invent quantities.

PLANS: [attach]
JOB TYPE: [paste]

Tip:Always spot-check 3 line items manually before pricing. Vision models can miscount — treat AI as the estimator's assistant, not the estimator.

[02]

Weekly job pipeline summary

AI compiles which jobs are running, which are delayed, which need follow-up, and what's owed in invoices — into a tight Friday-afternoon brief for the owner.

Time saved
90 min/week
Tool
Claude + your job spreadsheet
$ Starter prompt+
From the job tracker below, produce a Friday brief covering:

- Jobs running on schedule (one line each)
- Jobs slipping or at risk (with reason + recommended action)
- Quotes outstanding (need follow-up)
- Cash collection — invoices owed by who
- 3 priorities for next week

TRACKER: [paste]

Tip:Run Friday afternoon. You'll know your Monday before you finish your coffee.

[03]

End-of-job invoice + photo report

Final invoice assembled with photo evidence and a short description from your job notes. Clients pay faster when they see the work clearly documented.

Time saved
30 min per job
Tool
Claude with vision + your invoice template
$ Starter prompt+
Assemble a final invoice + completion report for the job below:

- Itemised invoice using the template in this project
- 4–6 best photos with one-line captions
- Short summary of work completed
- Warranty notes + payment terms

JOB NOTES: [paste]
PHOTOS: [attach]

Tip:Photo evidence cuts payment disputes in half. Clients pay 30%+ faster when they can see exactly what they're paying for.

[04]

Quote drafts from inbound enquiry

Voicemail or email enquiry → drafted quote letter using your rate sheet and standard inclusions. You eyeball, adjust, send.

Time saved
30–45 min per quote
Tool
Claude + voice-to-text (Whisper / Otter)
$ Starter prompt+
From the enquiry below and the rate sheet in this project, draft a quote letter that includes:

- Acknowledgement of what they asked for
- Itemised line items at YOUR rates
- Standard inclusions and exclusions
- Total + GST
- Validity (30 days) and next steps

Don't invent prices. If something isn't on the rate sheet, flag it for me.

ENQUIRY: [paste]

Tip:Keep your pricing rules in a workspace doc. Never let AI invent numbers.

[05]

Job photos → progress reports for clients

Daily site photos + a few sentences of notes → professional weekly progress update sent to the homeowner. Stops the 'how's it going?' calls.

Time saved
20 min per job per week
Tool
Claude with vision
$ Starter prompt+
From the photos and notes below, draft a 150-word weekly progress update for the homeowner at [address]:

- What got done this week
- What's planned for next week
- Anything they need to decide or pay for
- One photo highlight to call out

Tone: friendly, clear, no jargon.

PHOTOS + NOTES: [paste / attach]

Tip:Standardise the template once. Clients learn to expect Friday updates and stop the mid-week check-ins.

Want these built into your business?
We set up the whole AI workspace for you.
See packages

5 quick AI wins for distribution businesses.

For wholesale, B2B distribution, and supply businesses.

[01]

PDF order → structured order data

Customer PDFs and emails come in formatted however they like. AI extracts the order into your system's structure (SKU, qty, ship-to).

Time saved
5–10 min per order
Tool
Claude with vision (PDF reading)
$ Starter prompt+
Extract the order from the attached document into this exact JSON structure:

{
  "customer": "",
  "po_number": "",
  "ship_to": "",
  "ship_date_requested": "",
  "lines": [{ "sku": "", "description": "", "qty": 0, "unit_price": 0 }],
  "notes": ""
}

If anything is ambiguous, flag it. Don't invent SKUs.

DOC: [attach]

Tip:Build a 'common formats' workspace doc for your tricky customers — AI learns their quirks.

[02]

Daily stock alert summary

Stock data → daily summary of what's low, what's overstocked, what's at risk of running out before the next shipment.

Time saved
1 hr/day for the ops manager
Tool
Claude + spreadsheet
$ Starter prompt+
From the stock data and forward orders below, produce a 7am alert covering:

- SKUs likely to stock out in the next 14 days (with date + reason)
- SKUs overstocked (>90 days of cover)
- Orders that can't be fulfilled with current stock
- One recommended action per alert

DATA: [paste]

Tip:Run at 7am so it's waiting when the team opens up.

[03]

Returns / credit note processing

Return reason + photos → policy check + drafted credit note + customer reply with the right tone calibrated to fault. Removes hours of admin per week from your ops team.

Time saved
20 min per return
Tool
Claude with vision + your credit note template + returns policy
$ Starter prompt+
Process the return below:

1. Determine if a credit is warranted (apply policy in this project)
2. Draft the credit note using the template
3. Draft a reply email to the customer (apologise if our fault, neutral if not)

RETURN INFO: [paste + attach photos]

Tip:Tone differs by reason. 'Our fault' = warm apology. 'Their fault' = neutral and matter-of-fact.

[04]

Supplier follow-up sequence

AI drafts overdue PO follow-ups, escalations, and chase emails on the cadence you define — saves the back-and-forth of figuring out who to chase and how.

Time saved
2 hrs/week
Tool
Claude with your supplier escalation ladder
$ Starter prompt+
From the overdue PO list and escalation ladder in this project, draft today's outbound emails:

- 1st follow-up (7 days overdue): polite check-in
- 2nd follow-up (14 days): firmer, escalates to their manager
- 3rd follow-up (21+ days): formal, copies their account exec

POS: [paste]

Tip:Build a 'supplier escalation ladder' doc — your standard cadence per supplier tier.

[05]

Customer comms on delays / order status

When orders slip, AI drafts personalised update emails per customer — tone calibrated to the relationship (formal for some, casual for others).

Time saved
2–3 hrs/week
Tool
Claude with your customer relationship notes
$ Starter prompt+
Below are orders running late and the customer relationship notes for each. Draft a personalised email per customer covering:

- New ETA (be specific)
- Why (honest, brief)
- What you're doing about it
- Any concession if warranted

Tone: match the relationship — formal for X, casual for Y.

DELAYS: [paste]

Tip:Always review before sending. Customer comms are reputation — never auto-send delay emails.

Want these built into your business?
We set up the whole AI workspace for you.
See packages

Want help making it real?

Quick wins are a start. We come on-site, set up the whole AI workspace for your team, and keep it running. Three packages, from $2,400.