ZonifyMo is a proprietary AI-assisted analysis platform built to support structured parcel screening and preliminary development assessment across key markets.
ZonifyMo streamlines the earliest stages of deal evaluation, enabling faster movement from opportunity identification to informed decision-making.
Structured, AI-driven filtering across parcels by zoning type, lot dimensions, permitted density, and development potential.
Automated zoning code interpretation with overlay district detection, setback calculations, and use-right classification.
Composite scoring models that weigh zoning alignment, site constraints, and market conditions into a preliminary viability assessment.
Continuous monitoring across target geographies to surface parcels meeting custom-defined investment criteria.
Exportable preliminary assessment reports formatted for internal review, capital committee presentation, and deal tracking.
Source-linked data with audit trails ensuring every screening output maps back to verified municipal records and public data.
Four streamlined steps that collapse weeks of manual research into minutes of structured analysis.
Set target parameters including market area, zoning types, minimum lot size, and intended use.
AI scans available inventory across your target geography and flags parcels that meet your criteria.
Each flagged parcel receives automated zoning analysis with permitted uses, density, and setback data.
Parcels receive a composite feasibility score with exportable reports ready for internal review.
ZonifyMo is purpose-built for the markets where BlockStreet Properties operates, with localized zoning data and municipal code mappings.
Suburban infill, transit-oriented, and mixed-use development screening across key counties.
Growth corridor analysis and metropolitan-adjacent opportunity identification.
Sun Belt market scanning across high-growth regions with favorable regulatory conditions.
ZonifyMo is currently in development. Reach out to learn more about the platform and request early access.
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