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Australian Building Permit Data Is a Goldmine. Here's What We Built With It.

#api #python #data #startup

Every time someone in Australia wants to build a pool, knock down a house, or develop a block of townhouses, they submit a Development Application (DA) to their local council. That's public data -- 18,000+ applications across 330+ councils, updated daily.

Most people don't realise how powerful this data is when you combine it with other sources. I want to show you what I mean by walking through what we built with it, and then painting a picture of what's possible.

How We Use DA Data: The Feasibility Calculator

We built DA Leads to aggregate development applications from every Australian state. But aggregation alone isn't the interesting part.

The interesting part is what happens when you layer DA data on top of other data sources.

Take our feasibility calculator. When a property developer types in an address, here's what happens behind the scenes:

  1. We pull parcel boundaries and lot area from state cadastre services (7 different government GIS systems)
  2. We look up zoning and planning overlays -- heritage, flood, bushfire, height limits -- from state planning scheme layers
  3. We fetch median sale prices and recent comparables for the suburb
  4. We estimate dwelling capacity using Australian standards (ResCode, NCC setbacks, parking requirements)
  5. And then -- here's where our DA data comes in -- we pull nearby development applications to show what's actually being built in the area

That last piece changes the conversation. A developer isn't just looking at theoretical zoning capacity. They're seeing that 3 townhouse projects and 2 subdivisions were lodged within 1km in the last 6 months. That's a signal. It tells them this area is active, councils are approving similar projects, and there's market demand.

DA data became a module inside a larger product. Not the whole product -- a component that adds real-world context to financial modelling.

The Pattern: DA Data as a Signal Layer

Here's what I think most proptech companies are missing. DA data isn't just a list of building permits. It's a real-time signal of what's happening on the ground, and it can slot into almost any property or construction product as an enrichment layer.

Think about what a single DA record tells you:

  • Where construction is happening (address, council, state, coordinates)
  • What type of work (we AI-classify every DA into 21 trade categories -- renovation, pool, demolition, subdivision, etc.)
  • When it was lodged, and its current status
  • How much it might cost (estimated cost of development)
  • Who is doing it (applicant name on paid tier)

Now imagine layering that on top of what you already have.

What Could You Build?

If you're building a construction CRM:

Your users manage leads manually. What if new leads appeared automatically? A plumber in western Melbourne could wake up to 3 new pool DAs lodged yesterday within 15km. A demolition company gets pinged the moment a demo permit hits the system.

You don't need to build the data pipeline. You register a webhook, and new DAs push to your system in real time:

import requests

API_KEY = "dk_your_key"
BASE = "https://daleads.com.au/api/v1"
headers = {"Authorization": f"Bearer {API_KEY}"}

# Register a webhook -- get notified when new DAs appear
resp = requests.post(f"{BASE}/webhooks", headers=headers, json={
    "url": "https://yourapp.com/api/webhooks/new-da",
    "events": "new_da",
})
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Your CRM goes from "users enter leads" to "leads find users."

If you're building a property investment platform:

Your users analyse suburbs by rental yield and capital growth. But they can't see what's about to change. A suburb with a spike in subdivision DAs is about to get denser. An area where renovation DAs dominate is gentrifying. One where demolition permits are up might be transitioning from houses to apartments.

# What's happening in a specific suburb?
resp = requests.get(f"{BASE}/das", headers=headers, params={
    "suburb": "Brunswick",
    "state": "VIC",
    "since": "2025-10-01",
})

# Count by category to spot trends
from collections import Counter
categories = Counter(da["trade_category"] for da in resp.json()["data"])
# {'Renovation': 12, 'Subdivision': 8, 'Multi Dwelling': 5, ...}
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DA data becomes a leading indicator your competitors don't have.

If you're building a supply chain or logistics product for construction:

Material suppliers guess where demand is going. They shouldn't have to. If pool DAs are up 40% in Queensland this quarter, that's a concrete signal to stock more pool equipment in QLD warehouses. If renovation activity is clustered in inner-city Melbourne, that's where to position trade supply inventory.

# National stats -- where is construction happening?
stats = requests.get(f"{BASE}/stats", headers=headers).json()["data"]

for state in stats["by_state"]:
    print(f"  {state['state']}: {state['count']} DAs")

# Drill into a specific council
resp = requests.get(f"{BASE}/das", headers=headers, params={
    "council": "Brisbane City Council",
    "category": "Pools",
    "since": "2026-01-01",
})
print(f"Pool DAs in Brisbane this year: {len(resp.json()['data'])}")
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If you're building insurance or lending products:

New DAs signal new construction risk and new financing opportunities. A lender could automatically surface construction loan prospects. An insurer could monitor builder activity in bushfire overlay zones. The data is there -- it just needs to be connected.

Embed the Feasibility Calculator in Your Product

If you don't want to build anything from scratch but want to offer site analysis to your users, you can embed our feasibility calculator directly:

<iframe
  src="https://daleads.com.au/embed/feasibility"
  width="100%"
  height="800"
  frameborder="0"
></iframe>
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Your users get parcel lookups, zoning checks, dwelling capacity estimates, and financial modelling -- all pulling live government data from 7 state GIS systems. No API integration needed.

Getting Started

The DA data API uses Bearer token authentication. Get a free key at daleads.com.au/api.

Interactive docs: daleads.com.au/api/v1/docs

Plan Rate Limit Price
Free 100 req/day $0
Starter 1,000 req/day $199/mo
Pro 10,000 req/day $999/mo

The free tier is enough to prototype your integration and see if the data fits your use case.

The Bigger Point

We started DA Leads as a way to help tradies find building leads. But along the way, we realised the real value isn't in showing a list of DAs -- it's in what happens when DA data becomes one input into a larger system.

Our feasibility calculator is one example. Yours could be something completely different. The data is structured, categorised, and available via API. What you build on top of it is up to you.

I'm Bo, a solo developer in Melbourne. If you're working on a proptech product and want to explore what DA data could do for it, I'd genuinely like to hear your use case. Reach out or check out DA Leads.

Bo | GitHub

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