Inspiration

For small and medium-sized businesses, choosing where to open a new location is one of the highest-risk decisions they make.

The most successful expansions happen when businesses move into areas just before population growth and local demand accelerate. But today, early visibility into those shifts is unevenly distributed.

Large organisations rely on consultants, internal research teams, and private planning insight to anticipate where growth is coming. SMEs and family-run businesses are often forced to react later - once rents rise, competition increases, and the opportunity has already been priced in.

We built Zonary to level that playing field - by turning fragmented residential planning data into accessible, early yet fundamental indicators of where local demand is about to grow.


What it does

Zonary helps SMEs identify locations where residential growth - and therefore local demand - is likely to accelerate before it becomes obvious on the ground.

Instead of relying on footfall after the fact or expensive reports, Zonary uses planning behaviour as a leading signal for where people are about to move and settle.

Users select a location and radius, and Zonary:

  • Breaks the area into micro-regions to detect hyper-local planning changes
  • Generates a heatmap showing where residential development momentum is increasing
  • Scores regions based on:
    • New residential build momentum (where population growth is being unlocked)
    • Council approval behaviour (where planning resistance is decreasing, signalling a shift in policy or alignment)
    • Income resilience (whether new housing can be absorbed into sustained local demand)
  • Ranks the top postcodes within the area
  • Surfaces real property listings so businesses can act early
  • Provides AI-generated explanations that translate planning data into plain-English location rationale

Rather than showing where demand already exists, Zonary reveals where demand is about to arrive - helping SMEs expand into areas with growing customer bases, before competition and costs catch up.


How we built it

We built Zonary as a client-side web application using:

  • React + TypeScript for the frontend
  • Vite for fast iteration
  • Map-based visualisation for spatial analysis and heatmaps
  • Serac / IBex APIs to retrieve residential planning data, including:

    • Project types (small, medium, large residential)
    • Approval rates
    • Property type
  • External datasets for median income to estimate demand absorption

  • Lightweight AI analysis via Gemini API to summarise patterns and explain scores in natural language


Challenges we ran into

  • Data constraints:
    The available planning data focused on residential project types, which required us to pivot away from business-use forecasting and refine our insight around residential growth instead, and it's knock-on market impact on business.

  • Avoiding noise:
    Planning data is dense and fragmented. A major challenge was designing metrics that captured structural change (representing more fundamental growth) rather than raw activity.


Accomplishments that we're proud of

  • Identifying and operationalising planning approval behaviour as a leading indicator of residential growth
  • Designing a system that highlights constraint relaxation, not just development volume
  • Building a product that moves users from insight → action in one flow
  • Creating analytics based on fundamental market truths that remain accessible to SMEs and independent investors

What we learned

  • Planning systems embed powerful early signals - but they’re rarely analysed at a micro-geographic level. Finding granular data at that scale is hard!
  • Approval rates and decision speeds can be more informative than raw application counts.
  • Median income is most valuable when framed as absorption capacity, not generic demand
  • Less data, used intentionally, often produces clearer insight than overly complex dashboards.

What's next for Zonary

Next steps include:

  • Incorporating unit-level data (e.g. number of bedrooms, not just homes)
  • Adding additional constraint layers such as conservation areas or flood risk
  • Developing alerting and monitoring features for ongoing planning regime shifts - defo a cool tool to buildto alert investors as soon as possible

Our long-term vision is to make early planning intelligence — once locked behind consultants and relationships — available to anyone making residential investment decisions.

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